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This paper attempts to systematize natural language analysis process by (I) use of a partitioned semantic network formalism as the meaning representation and (2) stepwise translation based on Montague Grammar. …...

This paper discusses the linguistic and computational techniques employed in the current version of Machine Translation system being developed at the Linguistics Research Center of the University of Texas, under …...

A proper treatment of syntax and semantics in machine translation is introduced and discussed from the empirical viewpoint. For English- Japanese machine translation, the syntax directed approach is effective where …...

Our MT systems integrate many advanced con- cepts from the fields of computer science, linguis- tics, and AI : specialized languages for linguistic programming based on production systems, complete linguistic …...

The GTI~syst~m is a tree-to-tree transducer developed for teaching purposes in machine transla- tion. The transducer is a specialized production system giving the linguists the tools for express- ing infon~ation …...

The difficulties to be met with the resolu- tion of syntactical ambiguity in MT can be at least partially overcome by means of preserving the syntactical ambiguity of the source …...

Elements ot the history, state of the art, and probable future of Machine Translation (MT) are discussed. The treatment is largely tutorial, based on the assumption that this audience is, …...

In this paper we will present three systems, ATLAS, THAM and VISULEX, which have been designed and implemented at GETA (Study Group for Machine Translation) in collaboration with IFCI (Institut …...

Starting from the assumption that machine translation (MT) should be based on theoretically sound grounds, we argue that, given the state of the art, the only viable solution for the …...

This paper proposes an analysis method for Japanese modality. In this purpose, meaning of Japanese modality is classified into four semantic categories and the role of it is formalized into …...

This report outlines a machine translation system whose linguistic component is based on principles of Government and Binding. A "universal grammar" is defined, together with pal-ameters of variation for specific …...

This paper describes a prototype English-Japanese machine translation (MT) system developed at the Sci- ence Institute of IBM Japan, Ltd. This MT system cur- rently aims at the translation of …...

Building on the well-established premise that reliable machine translation requires a significant degree of. text comprehension, this paper presents a recent advance in multi-lingual knowledge- based machine translation (KBMT). Unlike …...

A crucial test for any MT system is its power to solve lexical ambiluities. The size of the lexicon, its structural principles and the availability of extra-lin_~istic knowled~q are the …...

This paper presents a transfer framework called LFT (Lexical-functional Transfer) for a machine translation system based on LFG (Lexical-functional Grammar). The translation process consists of subprocesses of analysis, transfer and …...

The purpose of this contribution is to formulate ways in which the homonymy of so- called 'Modal Particles' and their etymons can be handled. Our aim is to show that …...

The analysis phase in an indirect, transfer and global approach to machine translation is studied. The analysis conducted can be described as exhaus- tive (meaning with backtracking), depth-first and strategically …...

This paper looks at the use in machine Translation systems of the linguistic models of Case and Valency. It is argued that neither of these models was originally developed with …...

We are developing stylistic grammars to provide the basis for a French and English stylistic parser. Our stylistic grammar is a branching stratificational model, built upon a foundation dealing with …...

We sketch and illustrate an approach to machine translation that exploits the potential of simultaneous correspondences between separate levels of linguistic representation, as formalized in the LFG notion of codescriptions. …...

AbstractIBM is engaged in advanced research and development projects on various aspects of machine translation, between several language pairs. The activities reported on hero are all parts of a rather …...

AbstractThis paper outlines a new architecture for a NLP/MT development environment for the EUROTRA project, which will be fully operational in the 1993-94 time frame. The proposed architecture provides a …...

AbstractThis presentation outlines the implementation of a machine translation system for avalanche warning bulletins in natural language, using a unification-based formalism developed at ISSCO, which will be introduced at the …...

AbstractWe describe an interlingua-based approach to machine translation, in which a DRS representation of the source text is used as the interlingua representation. A target DRS is then created and …...

AbstractAll human languages are open and complex communication systems. No machine translation system will ever be able to automatically translate all possible sentences from one language to another in high …...

We wrote this report in Japanese and trans- lated it by NEC's machine translation system PIVOT/JE.) IBS (International Business Service) is the com- pany which does the documentation service which …...

AbstractWe wrote this report in Japanese and translated it by NEC's machine translation system PIVOT/JE.) IBS (International Business Service) is the company which does the documentation service which contains translation …...

AbstractRecently, several types of Japanese to English MT (machine translation) systems have been developed, but prior to using such systems, they have required a pre-editing process of re-writing the original …...

AbstractULTRA (Universal Language TRAnslator) is a multilingual, interlingual machine translation system currently under development at the Computing Research Laboratory at New Mexico State University. It translates between five languages (Chinese, …...

AbstractLinguistic engineering presupposes lexical resources. For translation, it is highly desirable that a Machine Translation engine and human translators should have access to the same dictionary information. The present paper …...

AbstractIn this paper, we introduce the methodology for the construction of dictionary fragments under development in DELIS. The approach advocated is corpus-based, computationally supported, and aimed at the construction of …...

AbstractTyped feature formalisms (TFF) play an increasingly important role in NLP and, in particular, in MT. Many of these systems are inspired by Pollard and Sag’s work on Head-Driven Phrase …...

This note introduces at, English-to-Korean Machiue 'lYanslation System MA!t'ES/EK, which ha.s been de- veloped as a research prototype and is still under up- grading in KAIST (Korea Advanced Institute of …...

A method for generating a machine translation (MT) dictionary from parallel texts is described. This method utilizes both statistical information and linguistic information to obtain corresponding words or phrases in …...

This paper presents a heuristic method that uses information in the Japanese text along with knowledge of English countability and number stored in transfer dictionaries to de- termine the countability …...

A methodology is presented for coml)onent-l)ase(l machine translation (MT) evaluation through causal error analysis to complement existing global evalu- ation methods. This methodology is particularly :q)- propriate for knowledgc-I)ased machine …...

This paper outlines customization of a machine translation system using translation templates, which enable usm~ to represent the bilingual knowledge needed for complex translation. To evaluate their effectiveness, we analyzed …...

We discuss some key methodological and operational aspects related to the design and development of a machine translation (MT) prototype which can be integrated in healthcare information systems. We first …...

in this paper, we describe the acquisition iuld (Irga- nization of knowledge sources fur machine translation (MT) systems. It has heen liointed out by many users that one of the …...

The authors propose a model for analyz- ing English sentences including coordinate conjunctions such as "and", "or", "but" and the equivalent words. Syntactic analysis of the English coordinate sentences is …...

This paper describes the enhancements made, within a unification framework, based on typed feature structures, in order to support linking of lexical entries to their translation equivalents. To help this …...

This paper will focus on the semantic representa- tion of verbs in computer systems and its impact on lexical selection problems in machine transla- tion (MT). Two groups of English …...

. In the course of four evaluations in the Advanced Research Projects Agency Machine Translation series, evaluation methods have evolved for measuring the core components of a diverse set of …...

Factors for success and failure in Machine Translation are extracted from an analysis of the 50 years history of MT. Situations are different in various types of MT (MT for …...

This paper describes a method of evaluating quality for developers of machine translation systems to easily check imperfections in their own systems. This evaluation method is a systematic, objective method …...

: Based on the long-standing experience with the project Logic-Programm- ing based Machine Translation (LMT), IBM and the publisher von Rheinbaben & Busch have developed Personal Translator®, a machine translation …...

I'rel)ositional l'hrase is the key issue in structuraJ ambiguity, l{ecently, re- searches in corpora provide the lexical cue of pre[)ositions with other words and the information could be used to …...

This l)a.i)cr t)rot)oses ;m mmlysis of clas- sifters into ['our ma,jor l;yl)(;s: t0Nl'l', ME'I't(I(1, (III()UI' il,lld SPI,;(',IES, ])~lS(!(1 Oil prot)('xl;ies ()[ l)ol,h .la.l/a.tw, s(~ and 10,u - glish. Tlm nnalysis …...

We describe a number of experiments that demonstrate the usefulness of prosodic information for a processing module which parses spoken utterances with a feature-based grammar employing empty categories. We show …...

The development of natural language pro- ccssing (NLP) systems that perform ma- chine translation (MT) and information re- trieval (IR) has highlighted the need for the automatic recognition of proper …...

This paper proposes the use of "pattern- based" context-free grammars as a basis for building machine translation (MT) sys- tems, which are now being adopted as per- sonal tools by …...

This article presents a new semantic- based transfer approach developed and applied within the Verbmobil Machine Translation project. We give an overview of the declarative transfer formalism to- gether with …...

Semantic representations which are underspecified with respect to, for example, scope, have recently attracted much attention. Most research in this area has focused on treating English language phenomena in a …...

AbstractThis tutorial provides a nontechnical introduction to machine translation. It reviews the whole scope of MT, outlining briefly its history and the major application areas today, and describing the various …...

This paper describes the design and imple- mentation of an English-Turkish machine translation (MT) system developed as a part of the TU-Language project supported by a NATO Science for Stability …...

Automatic segmentation of text into min- imal content-bearing units is an unsolved problem even for languages like English. Spaces between words offer an easy first ap- proximation, but this approximation …...

AbstractA successful MT operation is the result of good planning, an incremental approach, dedicated and talented people, and MT software that is capable of handling the types of text to …...

We focus on the probleln of building large repositories of le.rical coJtceplual structure (LCS) representations for verbs in multi- ple languages. One of the main results of this work is …...

We examine the Differential Grammar, a representation designed to discriminate which of a set of eonfusable alternatives is most likely in the context it occurs in. This approach is useful …...

We classify and review current approaches to software infrastructure for research, de- velopment and delivery of NLP systems. The task is motivated by a discussion of current trends in the …...

The previous English-Korean MT system that was the transfer-based MT system and applied to only written text enumerated a following brief list of the problems that had not seemed to …...

Bilingual news article alignment methods based on multi-lingual information retrieval have been shown to be successful for the automatic production of so-called noisy-parallel corpora. In this paper we compare the …...

Bilingual news article alignment methods based on multi-lingual information retrieval have been shown to be successful for the automatic production of so-called noisy-parallel corpora. In this paper we compare the …...

AbstractIn this paper, I present a method for the evaluation of the quality of translated text, namely, a translation ability index, which shows the relative position of the translation ability …...

AbstractWe describe a Machine Translation framework aimed at the rapid development of large scale robust machine translation systems for assimilation purposes, where the MT system is incorporated as one of …...

AbstractThis paper describes an ongoing project which has the goal of improving machine translation quality by increasing knowledge about the text to be translated. A basic piece of such knowledge …...

AbstractFor efficiency reasons, Machine Translation systems are generally designed to eliminate ambiguities as early as possible even if delaying the decision would make a more informed choice possible. This paper …...

AbstractThe machine translation (MT) system came out brilliantly. Today, however, the development of the MT system is losing the vigor it once had. The cause of the system’s infrequent use …...

This paper proposes a new model of machine translation system in which rule-based and example-based approaches are applied for English-to-Thai sentence translation. The proposed method has 4 steps :1) analyze …...

AbstractThere have been substantial changes in computing practices in the cyberspace, mainly as a result of the proliferation of low priced under-utilized powerfully heterogeneous computers are connected by high-speed links. …...

AbstractThis survey of the situation regarding the R&D of machine translation in China concentrates on how the design and application of MT systems could be on the shadow of the …...

In this paper we describe an implemented framework for developing monolingual or multilingual natural language generation (NLG) applications and machine translation (MT) applications. The framework demonstrates a uniform approach to …...

Language technology (LT) plays an increasingly important role in the field of multilingual information content production and knowledge management. Companies are more and more faced with the problem of the …...

Advances in machine translation are becoming increasingly dependent on the availability of large scale language resources, in particular parallel corpora. The talk presents Slovene-English language resources that were developed as …...

We present a machine learning approach to evaluating the well- formedness of output of a machine translation system, using classifiers that learn to distinguish human reference translations from machine translations. …...

AbstractThis paper describes a program that automatically selects the best translation from a set of translations produced by multiple commercial machine translation engines. The program is simplified by assuming that …...

AbstractEvaluation of machine translation is one of the most important issues in this field. We have already proposed a quantitative evaluation of machine translation system. The method was roughly that …...

Knowledge acquisition is a bottleneck in machine translation and many NLP tasks. A method for automatically acquiring translation templates from bilingual corpora is proposed in this paper. Bilingual sentence pairs …...

This paper introduces a set of guidelines for annotating time expressions with a canonicalized representation of the times they refer to. Applications that can benefit from such an annotated corpus …...

This paper describes an approach to Machine Translation that places linguistic information at its foundation. The difficulty of translation from English to Japanese is illustrated with data that shows the …...

AbstractNowadays, there is a growing need for dissemination of documents in several languages. Machine translation is usually regarded as a possible solution for this, but so far it cannot provide …...

Real (i.e., working) machine translation may be presented both as the result of inevitable approximations over an ideal, theoretically motivated model based on the principle of semantic compositionality and as …...

Information extraction (IE) systems are costly to build because they require development texts, pars- ing tools, and specialized dictionaries for each ap- plication domain and each natural language that needs …...

We consider the problem of parsing non-recursive context-free grammars, i.e., context-free grammars that generate finite languages. In natural language process- ing, this problem arises in several areas of application, including …...

A number of machine translation systems based on the learning algorithms are presented. These methods acquire translation rules from pairs of similar sentences in a bilingual text cor- pora. This …...

We discuss a framework for teaching con- trastive translation-oriented linguistics to students of machine translation. The frame- work embodies a classification of cross- linguistic differences and a demonstration of how …...

The paper describes the use of an assessed independent study project on machine translation evaluation as part of a final-year undergraduate course on machine assisted translation. The advantages and potential …...

The different factors that affect the level of teaching of machine translation, both as a formal courseware and in an informal manner to students doing developmental and research projects can …...

This article reports on three cases of teaching translation or English as a foreign language using pre-editing tasks with a machine translation system. Trainee translators or English learners were asked …...

This paper reports the results of research into the current state of affairs with respect to teaching MT/CAT tools in Greece. Although a variety of methods is employed, this research …...

This paper discusses the role that can be played in teaching machine translation (MT) by free on-line MT services, emphasising the advantages that they offer for didactic purposes as well …...

Machine translation can play an impor- tant role nowadays, helping communica- tion between people. One of the projects in this field is TransType2 1. Its purpose is to develop an …...

When machine translation (MT) knowl- edge is automatically constructed from bilingual corpora, redundant rules are acquired due to translation variety. These rules increase ambiguity or cause incorrect MT results. To …...

In this paper we report on the set of con- trolled language specifications defined for Modern Greek and the development of the respective style checker. We will focus on the …...

It is a general assumption that 1) the readability and clarity of LSP texts written in a controlled language are better than uncontrolled texts and 2) that controlled languages produce …...

This paper describes a project currently under way at SAP dealing with the task of post-editing MT output. As a concrete re- sult of the project, a standard post-editing guide …...

Today, corpus plays an important role in development and evaluation language and speech technologies, such as part of speech tagging, parsing, word sense disambiguation, text categorization, named entity classification, information …...

. We describe a Machine Translation (MT) approach that is specifically designed to enable rapid development of MT for languages with limited amounts of online resources. Our approach assumes the …...

We present a novel automatic approach to constructing a bilingual semantic network—the BiFrameNet, to enhance statistical and transfer-based machine translation systems. BiFrameNet is a frame semantic representation, and contains semantic …...

In this paper, we discuss the performance of cross- lingual information extraction systems employing an automatic pattern acquisition module. This mod- ule, which creates extraction patterns starting from a user’s …...

This paper proposes a new paradigm for senti- ment analysis: translation from text documents to a set of sentiment units. The techniques of deep language analysis for machine translation are …...

We report on the results of an experiment aimed at enabling a machine translation system to select the appropriate strategy for dealing with words and phrases which have different translations …...

This paper presents example-based machine translation (MT) based on syntactic trans- fer, which selects the best translation by us- ing models of statistical machine translation. Example-based MT sometimes generates in- …...

In this paper we report on the results of an experiment in designing resource-light metrics that predict the potential translation complexity of a text or a corpus of homogenous texts …...

. We present an approach to the machine translation of French to Arabic in which we explain each of the different steps and some of the problems encountered at each …...

New words such as names, technical terms, etc appear frequently. As such, the bilingual lexicon of a machine translation system has to be constantly updated with these new word translations. …...

We report on the development of a cross lan- guage information retrieval system, which translates user queries by categorizing these queries into terms listed in a controlled vo- cabulary. Unlike …...

In order to boost the translation quality of corpus-based MT systems for speech transla- tion, the technique of splitting an input sen- tence appears promising. In previous re- search, many …...

This article studies different aspects of a new approach for word sense disambiguation using statistical information gains from a target language monolingual corpus. Here, the source language is English and …...

. How can recent advances in automating the evaluation of machine translation (MT) engines be applied to automate the evaluation of more complex embedded MT systems? In this paper, we …...

This paper addressees the problem of eliminat- ing unsatisfactory outputs from machine trans- lation (MT) systems. The authors intend to eliminate unsatisfactory MT outputs by using confidence measures. Confidence measures …...

. Most current Machine Translation (MT) systems do not improve with feedback from post-editors beyond the addition of corrected translations to parallel training data (for statistical and example-base MT) or …...

This paper presents a maximum entropy word alignment algorithm for Arabic- English based on supervised training data. We demonstrate that it is feasible to cre- ate training material for problems …...

We present a new approach to aligning sentences in bilingual parallel corpora based on punctuation, especially for English and Chinese. Although the length-based approach produces high accuracy rates of sentence …...

. We present the current status of development of an open-source shallow-transfer machine translation engine for the Romance languages of Spain (the main ones being Span- ish, Catalan and Galician) …...

. User acceptance and system integration in existing IT environments are the key factors in machine translation (MT) becoming a universally implemented tool. Although output quality obviously plays a major …...

. Ambiguous words pose very serious problems to existing machine translation systems. The Translation Checker, a system part of Translution Central addresses this prob- lem by allowing users to disambiguate …...

. This paper describes how word alignment information makes machine translation more effi- cient. Following a statistical approach based on finite-state transducers, we perform reordering of source sentences in training …...

. Machine Translation (MT) is the focus of extensive scientific in- vestigations driven by regular evaluation campaigns, but which are mostly oriented towards a somewhat artificial task: translating news articles …...

In this paper, we use the information re- dundancy in multilingual input to correct errors in machine translation and thus im- prove the quality of multilingual sum- maries. We consider …...

. The paper presents the design concept of the VoiceTRAN Communicator that in- tegrates speech recognition, machine translation and text-to-speech synthesis using the DARPA Galaxy architecture. The aim of the …...

Machine translation (MT) is a complex and a difficult task. It is not possible to achieve human competing performance with the present state of technology. Automating the process of translation …...

. Offering Machine Translation (MT) as a commercial service to end users means having to build up and regularly update large lexicons that can handle both general lan- guage and …...

. We describe a new approach for synthetically combining the output of several different Machine Translation (MT) engines operating on the same input. The goal is to pro- duce a …...

. The Prague Czech-English Dependency Treebank (PCEDT) is a syntactically annotated Czech-English parallel corpus. The Penn Treebank has been translated to Czech, and its annotation automatically transformed into dependency annotation …...

. In this paper we investigate the possibility of evaluating MT quality and fluency at the sentence level in the absence of reference translations. We measure the correlation between automatically-generated …...

. We propose the design, implementation and evaluation of a novel and modular approach to boost the translation performance of existing, wide-coverage, freely available machine translation systems based on reliable …...

This paper describes our recent work on integrating speech recognition and machine translation for improving speech translation performance. Two approaches are applied and their performance are evaluated in the workshop …...

In this paper we propose an approach to corpus-based generation in a machine translation framework that is similar to shake & bake (Whitelock, 1992). A bag of words is mapped …...

. Mining terminology translation from a large amount of Web data can be applied in many fields such as reading/writing assistant, machine translation and cross-language information retrieval. How to find …...

Translation of discontinuous phrases is a major challenge in Machine Trans- lation. Within METIS-II we developed a dictionary lookup strategy by mapping the items of a dictionary entry on non-adjacent …...

. To make it easier to understand the machine translation evaluation results, a curve is utilized to stand for the performance of a machine translation system. The position of the …...

. Multiple target translations are due to several meanings of source words, and various target word equivalents depending on the context of the source word. Thus, an automated approach is …...

AbstractWhen response metrics for evaluating the utility of machine translation (MT) output on a given task do not yield a single ranking of MT engines, how are MT users to …...

. The ready availability of free online machine translation (MT) systems has given rise to a problem in the world of language teaching in that students – especially weaker ones …...

In this paper, we argue that n-gram lan- guage models are not sufficient to address word reordering required for Machine Trans- lation. We propose a new distortion model that can …...

This paper presents an extensive evalua- tion of five different alignments and in- vestigates their impact on the correspond- ing MT system output. We introduce new measures for intrinsic evaluations …...

AbstractIn this paper we describe a set of processes for the acquisition of re­sources for quick ramp­up machine translation (MT) from any language lacking significant machine tracta­ble resources into English, …...

. Long and complex sentences are normally “low translatable” sentences due to high ambiguity. We describe a methodology of handling such sentences in APTrans, - a system for machine translation …...

Japanese case markers, which indicate the gram- matical relation of the complement NP to the predicate, often pose challenges to the generation of Japanese text, be it done by a …...

. This paper presents an overview of websites that parody real online machine translation (MT) services, as their sole purpose is to amuse users by offering fun translations without any …...

AbstractWe propose and evaluate a new paradigm for machine translation of low resource languages via the learned surface transduction and paraphrase of multilingual glosses....

Evaluation of machine translation output is an important but difficult task. Over the last years, a variety of automatic evalua- tion measures have been studied, some of them like Word …...

Phrase-based statistical translation systems are currently providing excel- lent results in real machine translation tasks. In phrase-based statistical translation systems, the basic translation units are word phrases. An im- portant …...

AbstractDiscriminative training methods have recently led to significant advances in the state of the art of machine translation (MT). Another promising trend is the incorporation of syntactic information into MT …...

AbstractThis paper reports on an experiment investigating how effective free online machine translation (MT) is in helping Internet users to access the contents of websites written only in languages they …...

. The paper gives an overview of the evaluation methods of memory-based translation systems: Translation Memories (TM) and Example Based Machine Translation (EBMT) systems. After a short comparison with the …...

While it is generally agreed that Word Sense Disambiguation (WSD) is an application-dependent task, the great majority of systems pursue application-independent approaches. We propose a strategy to support WSD for …...

. In this paper an innovative approach is presented for MT, which is based on pat- tern matching techniques, relies on extensive target language monolingual corpora and em- ploys a …...

The quality of a sentence translated by a machine translation (MT) system is dif- ficult to evaluate. We propose a method for automatically evaluating the quality of each translation. In …...

AbstractIn this paper, we give a description of the machine translation system developed at DCU that was used for our second participation in the evaluation campaign of the International Workshop …...

. External methods for evaluating MT systems define various measures based on MT results and their usage. While operational systems are mostly evaluated since long by task- based methods, evaluation …...

A Bloom filter (BF) is a randomised data structure for set membership queries. Its space requirements fall significantly below lossless information-theoretic lower bounds but it produces false positives with some …...

Machine translation of a source language sentence involves selecting appropriate tar- get language words and ordering the se- lected words to form a well-formed tar- get language sentence. Most of …...

AbstractWe present the machine translation system used by L2F from INESC-ID in the evaluation campaign of the International Workshop on Spoken Language Translation (2007), in the task of translating spontaneous …...

Unknown words are a well-known hindrance to natural language applications. In particu- lar, they drastically impact machine transla- tion quality. An easy way out commercial translation systems usually offer their …...

. In this article we present machine translationness (MTness, henceforth) as an approach for MT evaluations, in contrast to the notion of human likeness which is the basic criteria for …...

The alignment problem—establishing links between corresponding phrases in two related sentences—is as important in natural language inference (NLI) as it is in machine transla- tion (MT). But the tools and …...

. In this paper, we focus on alignment of Czech and English tectogrammatical dependency trees. The alignment of deep syntactic de- pendency trees can be used for training transfer models …...

Chinese is a language that does not have mor- phological tense markers that provide explicit grammaticalization of the temporal location of situations (events or states). However, in many NLP applications …...

Trasl´an makes full use of MT during our translation workflow, where the raw output from our Machine Translation (MT) system is passed onto human translators who perform post-editing (if necessary) …...

. This paper presents two hybrid architectures combining rule- based and statistical machine translation (RBMT and SMT) technology. In the first case, several existing MT engines are combined in a …...

We compare three commercial Machine Translation (MT) systems, Power Translator Pro1, SYSTRAN2, and T1 Langenscheidt3, with the research hybrid, statistical and rule-based system, METIS-II, with respect to identification of idioms. …...

The state-of-the-art system combination method for machine translation (MT) is the word-based combination using confu- sion networks. One of the crucial steps in confusion network decoding is the align- ment …...

Although Machine Translation (MT) is a very active research field which is receiving an in- creasing amount of attention from the research community, the results that current MT sys- tems …...

In this paper, we give a description of the ma- chine translation system developed at DCU that was used for our participation in the eval- uation campaign of the Third …...

Although research in other languages is in- creasing, much of the work in subjectivity analysis has been applied to English data, mainly due to the large body of electronic re- …...

To realize high quality machine transla- tion, we proposed a Non-Compositional Language Model, and developed a sen- tence pattern dictionary of 226,800 pat- tern pairs for Japanese compound and complex …...

Electronic written texts used in computer- mediated interactions (e-mails, blogs, chats, etc) present major deviations from the norm of the language. This paper presents an comparative study of systems aiming …...

. Analysis of short message corpus is an important foundation for research of automatic short message processing technology. Based on large scale short message corpus, this paper firstly presents statistical …...

We present a new English→Czech machine translation system combining linguistically motivated layers of language description (as defined in the Prague Dependency Treebank annotation scenario) with statistical NLP ap- proaches. 1...

. This paper presents a language independent methodology for automatically extracting bilingual lexicon entries from the web without the need of resources like parallel or comparable corpora, POS tagging, nor …...

It is a challenging task to identify sentiment polarity of Chinese reviews because the re- sources for Chinese sentiment analysis are limited. Instead of leveraging only monolin- gual Chinese knowledge, …...

. This paper addresses our system which provides an effective method to write an English paper suitable for international conferences and analyze the system’s pros and cons through the user’s …...

Foreign name translations typically include multiple spelling variants. These variants cause data sparseness problems, increase Out-of-Vocabulary (OOV) rate, and present challenges for machine translation, information extraction and other NLP tasks. …...

Constraint satisfaction inference is pre- sented as a generic, theory-neutral infer- ence engine for machine translation. The approach enables the integration of many different solutions to aspects of the output …...

. Verb classifications have been used to support a number of practical tasks and ap- plications, such as parsing, information extraction, question-answering, and machine trans- lation. However, large-scale exploitation of …...

Bilingual dictionaries are vital resources in many areas of natural language processing. Numerous methods of machine translation re- quire bilingual dictionaries with large cover- age, but less-frequent language pairs rarely …...

Collocations constitute a subclass of multi-word expressions that are particu- larly problematic for machine translation, due 1) to their omnipresence in texts, and 2) to their morpho-syntactic proper- ties, allowing …...

We explore the adaptation of English resources and techniques for text sentiment analysis to a new language, Spanish. Our main focus is the modification of an existing English semantic orientation …...

. Identifying collocations in a text (e.g., break record) and correctly translating them (battre record vs. *casser record) represent key issues in machine translation, notably because of their prevalence in …...

We present a machine translation frame- work that can incorporate arbitrary fea- tures of both input and output sentences. The core of the approach is a novel de- coder based …...

Translation is an indispensable process for socioeconomic and cultural development in a multilingual society. The use of translation tools such as translation memories and machine translation systems can be beneficial …...

Recently novel MT evaluation metrics have been presented which go beyond pure string matching, and which corre- late better than other existing metrics with human judgements. Other research in this …...

This paper presents a feasibility study for im- plementing lexical morphology principles in a machine translation system in order to solve unknown words. Multilingual symbolic treat- ment of word-formation is …...

Even leaving aside concerns of cognitive plausibil- ity, incremental parsing is appealing for applications such as speech recognition and machine translation be- cause it could allow the incorporation of syntactic …...

The paper addresses the issue of MT knowledge acquisition and describes a new hybrid methodology for automatic extraction of multi-word nominal termi- nology. The approach is based on statisti- cal …...

This paper presents a few ideas of the Center for Translation Studies at University of Illinois on the present and future of human and machine transla­ tion. In particular, as …...

This paper describes the development of several machine translation systems for the 2009 WMT shared task evaluation. We only consider the translation between French and English. We describe a sta- …...

This paper presents three successful tech- niques to translate prepositions heading verbal complements by means of rich lin- guistic information, in the context of a rule-based Machine Translation system for …...

This paper describes some of the kinds of pre- dictable errors in Machine Translation (MT). It then discusses means of alerting end-users of MT to the possible presence of such …...

A machine translated sentence is seldom completely correct. Confidence measures are designed to detect incorrect words, phrases or sentences, or to provide an esti- mation of the probability of correctness. …...

AbstractThis paper describes our resource-building results for an eight-week JHU Human Language Technology Center of Excellence Summer Camp for Applied Language Exploration (SCALE-2009) on Semantically-Informed Machine Translation. Specifically, we describe …...

AbstractWe present a method for acquiring reliable predicate-argument structures from raw corpora for automatic compilation of case frames. Such lexicon compilation requires highly reliable predicate-argument structures to practically contribute to …...

AbstractIn Chinese texts, words composed of single or multiple characters are not separated by spaces, unlike most western languages. Therefore Chinese word segmentation is considered an important first step in …...

AbstractIdentification of transliterations is aimed at enriching multilingual lexicons and improving performance in various Natural Language Processing (NLP) applications including Cross Language Information Retrieval (CLIR) and Machine Translation (MT). This …...

AbstractWe describe a focused effort to investigate the performance of phrase-based, human evaluation of machine translation output achieving a high annotator agreement. We define phrase-based evaluation and describe the implementation …...

AbstractIn emergency situations it is crucial that instructions are straightforward to understand. For this reason a controlled language for crisis management (CLCM), based on psycholinguistic studies of human comprehension under …...

AbstractIn this paper we report a way of constructing a translation corpus that contains not only source and target texts, but draft and final versions of target texts, through the …...

AbstractThe paper describes some of the work carried out within the European funded project MEDAR. The project has three streams of activity: the technical stream, the cooperation stream and the …...

Cross-language document summarization is a task of producing a summary in one language for a document set in a different language. Ex- isting methods simply use machine translation for document …...

AbstractIn this paper we want to point out some issues arising when a natural language processing task involves several languages (like multi- lingual, multidocument summarization and the machine translation aspects …...

This paper proposes a novel semi- supervised word alignment technique called EMDC that integrates discrimina- tive and generative methods. A discrim- inative aligner is used to find high preci- sion …...

AbstractErrors in machine translations of English-Iraqi Arabic dialogues were analyzed at two different points in the systems? development using HTER methods to identify errors and human annotations to refine TER …...

This paper presents efficient algorithms for expected similarity maximization, which co- incides with minimum Bayes decoding for a similarity-based loss function. Our algorithms are designed for similarity functions that are …...

We present new results from a hybrid com- bination of rule-based machine translation (RBMT) with a variant of statistical ma- chine translation (SMT) that supports hier- archical structures and is …...

AbstractHerein, we present the process of developing the first Hungarian Dependency TreeBank. First, short references are made to dependency grammars we considered important in the development of our Treebank. Second, …...

AbstractIndia is a multilingual country where machine translation and cross lingual search are highly relevant problems. These problems require large resources- like wordnets and lexicons- of high quality and coverage. …...

AbstractThe development of technologies to address machine translation and distillation of multilingual broadcast data depends heavily on the collection of large volumes of material from modern data providers. To address …...

This paper proposes a method that lever- ages multiple machine translation (MT) engines for paraphrase generation (PG). The method includes two stages. Firstly, we use a multi-pivot approach to acquire …...

Machine translation evaluation methods are highly necessary in order to analyze the performance of translation systems. Up to now, the most traditional methods are the use of automatic measures such …...

AbstractAligning the NPs of parallel corpora is logically halfway between the sentence- and word-alignment tasks that occupy much of the MT literature, but has received far less attention. NP alignment …...

Plagiarism, the unacknowledged reuse of text, does not end at language boundaries. Cross-language plagiarism occurs if a text is translated from a fragment written in a different language and no …...

Producing a fluent ordering for a set of prenominal modifiers in a noun phrase (NP) is a problematic task for natural lan- guage generation and machine translation systems. We present …...

We present the Johns Hopkins Univer- sity submission to the 2010 WMT shared translation task. We describe processing steps using open data and open source software used in our submission, …...

AbstractMachine transliteration is used in a number of NLP applications ranging from machine translation and information retrieval to input mechanisms for non-roman scripts. Many popular Input Method Editors for Indian …...

AbstractIt is recognized that many evaluation metrics of machine translation in use that focus on surface word level suffer from their lack of tolerance of linguistic variance, and the incorporation …...

The article presents an attempt to auto- mate all data creation processes of a rule- based shallow-transfer machine translation system. The presented methods were tested on two fully functional translation …...

AbstractTranslation into the languages with relatively free word order has received a lot less attention than translation into fixed word order languages (English), or into analytical languages (Chinese). At the …...

The present article introduces a phrase- alignment approach that involves the processing of a small bilingual corpus in order to extract suitable structural infor- mation. This is used in the …...

We describe the development of a pro- totype of an open source rule-based Icelandic→English MT system, based on the Apertium MT framework and IceNLP, a natural language processing toolkit for …...

. The present paper proposes automatic error analysis methods that use patterns representing grammatical check points. Our method is comparable to or slightly outperforms conventional methods for automatic evaluation metrics. …...

This paper describes a novel approach aimed to identify a priori which subset of machine translation (MT) systems among a known set will produce the most reliable translations for a …...

In this paper, we propose that MT is an im- portant technology in crisis events, something that can and should be an integral part of a rapid-response infrastructure. By integrating …...

In this work, we tackle the task of ma- chine translation (MT) without parallel train- ing data. We frame the MT problem as a de- cipherment task, treating the foreign …...

Machine translation (MT) technology is becoming more and more pervasive, yet the quality of MT output is still not ideal. Thus, human corrections are used to edit the output for …...

Although Machine Translation is very popular for personal tasks, its use in lo- calization and other business applications is still very limited. The paper presents an experiment on the evaluation …...

Future improvement of machine transla- tion systems requires reliable automatic evaluation and error classification mea- sures to avoid time and money consuming human classification. In this article, we propose a …...

We investigate the problem of predicting the quality of a given Machine Translation (MT) output segment as a binary classifi- cation task. In a study with four different data sets …...

This paper describes a new, freely available, highly multilingual named entity resource for person and organisation names that has been compiled over seven years of large-scale multilingual news analysis combined …...

We present the results of a project of build- ing a lexical-functional grammar of Ay- mara, an Amerindian language. There was almost no research on Aymara in compu- tational linguistics …...

This paper describes the machine translation (MT) system developed by the Transducens Research Group, from Universitat d’Alacant, Spain, for the WMT 2011 shared transla- tion task. We submitted a hybrid …...

Started from the very beginning, Stemming has been playing significant roles in several Natural Language Processing Applications such as information retrieval (IR), machine translation (MT), morph analysis and deciding the …...

This paper describes the development of a web-service tool for the automatic extraction of Multi-word expressions lexicons, which has been integrated in a distributed platform for the automatic creation of …...

Enriching statistical models with linguis- tic knowledge has been a major concern in Machine Translation (MT). In mono- lingual data, adjuncts are optional con- stituents contributing secondarily to the meaning …...

Automatic post-editors (APEs) enable the re-use of black box machine translation (MT) systems for a variety of tasks where different aspects of translation are impor- tant. In this paper, we …...

Statistical-based methods are the preva- lent approaches for implementing machine translation systems today. However the resulted translations are usually flawed to some degree. We assume that a statisti- cal baseline …...

A machine learning mechanism is learned from human annotations in order to perform preference ranking. The mechanism operates on a sentence level and ranks the alternative machine translations of each …...

This paper investigates the feasibility of using crowd-sourcing services for the hu- man assessment of machine translation quality of translations into non-English tar- get languages. Non-expert graders are hired through …...

The current paper evaluates the performance of the PRESEMT methodology, which facilitates the creation of machine translation (MT) systems for different language pairs. This methodology aims to develop a hybrid …...

AbstractCollocations can be defined as words that occur together significantly more often than it would be expected by chance. Many natural language processing applications such as natural language generation, word …...

This paper presents the results of an ex- perimental pilot user study, focusing on the evaluation of machine-translated us- er-generated content by users of an on- line community forum and …...

AbstractThe logistics of collecting resources for Machine Translation (MT) has always been a cause of concern for some of the resource deprived languages of the world. The recent advent of …...

We present a sub-sentential alignment al- gorithm that relies on association scores between words or phrases. This algorithm is inspired by previous work on alignment by recursive binary segmentation and …...

There are many abbreviation and non-standard tokens in SMS and Twitter messages. Nor- malizing these non-standard tokens will ease natural language processing modules for these domains. Recently, character-level machine translation …...

AbstractArabic is a morphologically rich language, and Arabic texts abound of complex word forms built by concatenation of multiple subparts, corresponding for instance to prepositions, articles, roots prefixes, or suffixes. …...

Machine translation aims to generate a target sentence that is semantically equivalent to the source sentence. However, most of current statistical machine translation models do not model the semantics of …...

AbstractThis paper reports on the development of new language resources for the Pashto language, a very low-resource language spoken in Afghanistan and Pakistan. In the scope of a multilingual data …...

This paper presents a novel approach to pivot-based machine translation (MT): while the state-of-the-art uses two statisti- cal systems, this proposal treats the second system as a black box. Our …...

AbstractThis paper presents a large corpus created from the original Quranic text, where semantically similar or related verses are linked together. This corpus will be a valuable evaluation resource for …...

We report on an experiment to test the ef- ficacy of ‘controlled language’ authoring of technical documents in Japanese, with respect both to the readability of the Jap- anese source …...

AbstractDue to instant availability and low cost, machine translation is becoming popular. Machine translation mediated communication plays a more and more important role in international collaboration. However, machine translators cannot …...

AbstractParaphrases are alternative syntactic forms in the same language expressing the same semantic content. Speakers of all languages are inherently familiar with paraphrases at different levels of granularity (lexical, phrasal, …...

AbstractAn increased number of machine translation services are now available. Unfortunately, none of them can provide adequate translation quality for all input sources. This forces the user to select from …...

This paper describes a new method for cross- lingual textual entailment (CLTE) detection based on machine translation (MT). We use sub-segment translations from different MT systems available online as a …...

We present a global log-linear model for synchronous grammar induction, which is capable of incorporating arbitrary features. The parameters in the model are trained in an unsuper- vised fashion from …...

Human evaluation of machine translation quality is a key element in the develop- ment of machine translation systems, as automatic metrics are validated through correlation with human judgment. How- ever, …...

We explore the application of neural language models to machine translation. We develop a new model that combines the neural proba- bilistic language model of Bengio et al., rec- tified …...

Our field has seen significant improve- ments in the quality of machine translation systems over the past several years. The single biggest factor in this improvement has been the accumulation …...

AbstractMachine translation (MT) draws from several different disciplines, making it a complex subject to teach. There are excellent pedagogical texts, but problems in MT and current algorithms for solving them …...

We consider the task of tagging Arabic nouns with WordNet supersenses. Three approaches are evaluated. The first uses an expert- crafted but limited-coverage lexicon, Arabic WordNet, and heuristics. The second …...

Expensive feature engineering based on WordNet senses has been shown be useful for document level sentimentto classification. A plausible reason for such a performance improvement is the reduction in data …...

Most of the machine translation systems rely on a large set of translation rules. These rules are treated as discrete and independent events. In this short paper, we propose a …...

AbstractGenerating fluent and grammatical sentences is a major goal for both Machine Translation (MT) and second-language Grammar Error Correction (GEC), but there have not been a lot of cross-fertilization between …...

AbstractWith the increasing number of applications handling spontaneous speech, the needs to process spoken languages become stronger. Speech disfluency is one of the most challenging tasks to deal with in …...

Despite the overwhelming use of statistical language models in speech recognition, machine translation, and several other domains, few high probability guarantees exist on their generaliza- tion error. In this paper, …...

This paper evaluates the impact of ma- chine translation on the software localiza- tion process and the daily work of profes- sional translators when SMT is applied to low-resourced languages …...

The exchange between Translation Studies (TS) and Machine Translation (MT) has been relatively rare. However, given recent developments in both fields like increased importance of post-editing and reintegra- tion of …...

Learning from errors is a crucial aspect of improving expertise. Based on this no- tion, we discuss a robust statistical frame- work for analysing the impact of different error types …...

As a multilingual vendor, we have access to machine translation (MT) scoring and other evaluation data on a wide range of language combinations and content types; we also have experience …...

Genre classification has been found to improve performance in many applications of statistical NLP, including language modeling for spoken language, domain adaptation of statistical parsers, and machine translation. It has …...

When machine translation researchers par- ticipate in evaluation tasks, they typically design their primary submissions using ideas that are not genre-specific. In fact, their systems look much the same from …...

AbstractThis paper presents a novel task of cross-language authorship attribution (CLAA), an extension of authorship attribution task to multilingual settings: given data labelled with authors in language X, the objective …...

AbstractThis paper presents manual and automatic annotation experiments for a pragmatic verb tense feature (narrativity) in English/French parallel corpora. The feature is considered to play an important role for translating …...

AbstractThe recent popularity of machine translation has increased the demand for the evaluation of translations. However, the traditional evaluation approach, manual checking by a bilingual professional, is too expensive and …...

In this paper, we propose a new method for effective error analysis of machine translation (MT) systems. In previous work on error analysis of MT, error trends are often shown …...

It is often assumed that raw MT output requires post-editing if it is to be used for more than gisting purposes. However, we know little about how end users engage …...

AbstractIn this paper, we leverage the existence of dual subtitles as a source of parallel data. Dual subtitles present viewers with two languages simultaneously, and are generally aligned in the …...

This paper presents the use of consensus among Machine Translation (MT) systems for the WMT14 Quality Estimation shared task. Consensus is explored here by com- paring the MT system output …...

We present an extrinsic evaluation of crawlers of parallel corpora from multi- lingual web sites in machine translation (MT). Our case study is on Croatian to English translation in the …...

In this study we compare two machine translation devices on twelve machine translation medical- domain specific tasks, and two transliteration tasks, altogether involving twelve language pairs, including English-Chinese and English-Russian, …...

Recent human evaluation of machine translation has focused on relative pref- erence judgments of translation quality, making it difficult to track longitudinal im- provements over time. We carry out a …...

Machine Translation (MT) Quality Estimation (QE) aims to automatically measure the quality of MT system output without reference translations. In spite of the progress achieved in re- cent years, current …...

AbstractAbstract Meaning Representations (AMRs) are rooted, directional and labeled graphs that abstract away from morpho-syntactic idiosyncrasies such as word category (verbs and nouns), word order, and function words (determiners, some …...

AbstractIn order to improve the symbiosis between machine translation (MT) system and post-editor, it is not enough to know that the output of one system is better than the output …...

AbstractWhenever the quality provided by a machine translation system is not enough, a human expert is required to correct the sentences provided by the machine translation system. In such a …...

Randomized methods of significance test- ing enable estimation of the probability that an increase in score has occurred sim- ply by chance. In this paper, we examine the accuracy of …...

AbstractThis paper presents an evaluation of the use of machine translation to obtain and employ data for training multilingual sentiment classifiers. We show that the use of machine translated data …...

Typing has traditionally been the only in- put method used by human translators working with computer-assisted transla- tion (CAT) tools. However, speech is a nat- ural communication channel for humans …...

Paraphrase generation is widely used for various natural language processing (NLP) applications such as question answering, multi-document summarization, and machine translation. In this study, we identify the problems occurring in …...

. Bilingual lexicons play a vital role in cross-language information retrieval and machine translation. The manual construction of these lexicons is often costly and time consuming. Word alignment techniques are …...

AbstractHuman translators are the key to evaluating machine translation (MT) quality and also to addressing the so far unanswered question when and how to use MT in professional translation workflows. …...

. Statistical approaches used in machine translation (MT) require the availability of large parallel corpora for the task at hand. The relative scarcity of thes resources makes domain adaptation a …...

This work presents the new flexible Mul- tidimensional Quality Metrics (MQM) framework and uses it to analyze the per- formance of state-of-the-art machine trans- lation systems, focusing on “nearly accept- …...

AbstractWhen a computer-assisted translation (CAT) tool does not find an exact match for the source segment to translate in its translation memory (TM), translators must use fuzzy matches that come …...

Through using knowledge bases, ques- tion answering (QA) systems have come to be able to answer questions accurately over a variety of topics. However, knowl- edge bases are limited to …...

In this paper we present a method of detecting zero pronouns in Japanese clauses and identifying their antecedents using aligned sentence pairs from a Japanese-English bilingual corpus and open resource …...

In this paper we describe an approach to automatic cognate identification in mono- lingual texts using machine translation. This system was used as our entry in the 2015 ALTA shared …...

This paper presents the work done to port a deep-transfer rule-based machine trans- lation system to translate from a differ- ent source language by maximizing the ex- ploitation of existing …...

This paper presents a hybrid machine translation framework based on a pre- processor that translates fragments of the input text by using example-based ma- chine translation techniques. The pre- processor …...

This paper demonstrates the possibility to make an existing automatic error classi- fier for machine translations independent from the requirement of lemmatisation. This makes it usable also for smaller and …...

Machine Translation (MT) has advanced in re- cent years to produce better translations for clients’ specific domains, and sophisticated tools allow professional translators to obtain translations according to their prior …...

Many state-of-the-art Machine Translation (MT) evaluation metrics are complex, in- volve extensive external resources (e.g. for paraphrasing) and require tuning to achieve best results. We present a simple alternative approach …...

This paper presents a machine transla- tion tool – based on Moses – developed for the International Maritime Organiza- tion (IMO) for the automatic translation of documents from Spanish, French, …...

This paper revisits the work of (Kuncham et al., 2015) which developed a statistical sandhi splitter (SSS) for agglutinative languages that was tested for Telugu and Malayalam lan- guages. Handling …...

We describe effort to improve machine translation of item titles found in a large e-commerce inventory through topic modeling and adaptation. Item titles are short texts which typically contain brand …...

Multiple references in machine transla- tion evaluation are usually under-explored: they are ignored by alignment-based met- rics and treated as bags of n-grams in string matching evaluation metrics, none of …...

AbstractMorphological analysis is a fundamental task in natural-language processing, which is used in other NLP applications such as part-of-speech tagging, syntactic parsing, information retrieval, machine translation, etc. In this paper, …...

AbstractThe paper steps outside the comfort-zone of the traditional NLP tasks like automatic speech recognition (ASR) and machine translation (MT) to addresses two novel problems arising in the automated multilingual …...

AbstractIn this paper, we propose a new annotation approach to Chinese word segmentation, part-of-speech (POS) tagging and dependency labelling that aims to overcome the two major issues in traditional morphology-based …...

AbstractEstimating similarities at different levels of linguistic units, such as words, sub-phrases and phrases, is helpful for measuring semantic similarity of an entire bilingual phrase. In this paper, we propose …...

AbstractVarious lexical resources are being published in RDF. To enhance the usability of these resources, identical resources in different data sets should be linked. If lexical resources are described in …...

AbstractComparable corpora are the main alternative to the use of parallel corpora to extract bilingual lexicons. Although it is easier to build comparable corpora, specialized comparable corpora are often of …...

AbstractIn this document we report on a user-scenario-based evaluation aiming at assessing the performance of machine translation (MT) systems in a real context of use. We describe a sequel of …...

AbstractThis paper discusses a methodology to measure the usability of machine translated content by end users, comparing lightly post-edited content with raw output and with the usability of source language …...

AbstractCross-lingual sentiment classification (CLSC) seeks to use resources from a source language in order to detect sentiment and classify text in a target language. Almost all research into CLSC has …...

Poorly translated text is often disfluent and difficult to read. In contrast, well-formed translations require less time to process. In this paper, we model the differences in reading patterns of …...

AbstractNeural network training has been shown to be advantageous in many natural language processing applications, such as language modelling or machine translation. In this paper, we describe in detail a …...

AbstractIn the present paper, we analyse variation of discourse phenomena in two typologically different languages, i.e. in German and Czech. The novelty of our approach lies in the nature of …...

We focus on two leading state-of-the-art approaches to grammatical error correc- tion – machine learning classification and machine translation. Based on the com- parative study of the two learning frame- …...

AbstractExisting approaches for evaluating word order in machine translation work with metrics computed directly over a permutation of word positions in system output relative to a reference translation. However, every …...

Recurrent neural network language models (RNNLM) have recently demonstrated vast potential in modelling long-term dependen- cies for NLP problems, ranging from speech recognition to machine translation. In this work, we …...

AbstractInteractive-predictive machine translation (IPMT) is a translation mode which combines machine translation technology and human behaviours. In the IPMT system, the utilization of the prefix greatly affects the interaction efficiency. …...

AbstractHuman-targeted metrics provide a compromise between human evaluation of machine translation, where high inter-annotator agreement is difficult to achieve, and fully automatic metrics, such as BLEU or TER, that lack …...

Structured prediction from bandit feed- back describes a learning scenario where instead of having access to a gold standard structure, a learner only receives partial feedback in form of the …...

AbstractEvaluating the quality of output from language processing systems such as machine translation or speech recognition is an essential step in ensuring that they are sufficient for practical use. However, …...

AbstractLight verb constructions (LVC) in Hindi are highly productive. If we can distinguish a case such as nirnay lenaa ‘decision take; decide’ from an ordinary verb-argument combination kaagaz lenaa ‘paper …...

AbstractThe present article reports on efforts to improve the translation accuracy of a corpus―based Machine Translation (MT) system. In order to achieve that, an error analysis performed on past translation …...

AbstractEvaluation of machine translation (MT) into morphologically rich languages (MRL) has not been well studied despite posing many challenges. In this paper, we explore the use of embeddings obtained from …...

AbstractIn this paper we combine two strands of machine translation (MT) research: automatic post-editing (APE) and multi-engine (system combination) MT. APE systems learn a target-language-side second stage MT system from …...

AbstractParallel corpora are crucial for machine translation (MT), however they are quite scarce for most language pairs and domains. As comparable corpora are far more available, many studies have been …...

AbstractLanguage resources (LR) are indispensable for the development of tools for machine translation (MT) or various kinds of computer-assisted translation (CAT). In particular language corpora, both parallel and monolingual are …...

AbstractThis work presents parallel corpora automatically annotated with several NLP tools, including lemma and part-of-speech tagging, named-entity recognition and classification, named-entity disambiguation, word-sense disambiguation, and coreference. The corpora comprise both …...

AbstractWord Sense Disambiguation (WSD) is one of the open problems in the area of natural language processing. Various supervised, unsupervised and knowledge based approaches have been proposed for automatically determining …...

AbstractThis paper reports on an experiment where 795 human participants answered to the questions taken from second language proficiency tests that were translated to their native language. The output of …...

AbstractThis paper describes a two-step machine translation system that addresses the issue of translating into a morphologically rich language (English to Czech), by performing separately the translation and the generation …...

AbstractAutomatic evaluation of Machine Translation (MT) is typically approached by measuring similarity between the candidate MT and a human reference translation. An important limitation of existing evaluation systems is that …...

AbstractThis paper presents an approach combining lexico-semantic resources and distributed representations of words applied to the evaluation in machine translation (MT). This study is made through the enrichment of a …...

We introduce and describe the results of a novel shared task on bandit learning for machine translation. The task was orga- nized jointly by Amazon and Heidelberg University for the …...

The main aim of this paper is to investigate automatic quality assessment for spoken language translation (SLT). More precisely, we investigate SLT errors that can be due to transcription (ASR) …...

While recent changes in Machine Trans- lation state-of-the-art brought translation quality a step further, it is regularly ac- knowledged that the standard automatic metrics do not provide enough insights to …...

This paper presents the results of the WMT17 shared tasks, which included three machine translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and run-time es- timation of …...

AbstractMonolingual evaluation of Machine Translation (MT) aims to simplify human assessment by requiring assessors to compare the meaning of the MT output with a reference translation, opening up the task …...

AbstractMachine translation (MT) quality is evaluated through comparisons between MT outputs and the human translations (HT). Traditionally, this evaluation relies on form related features (e.g. lexicon and syntax) and ignores …...

AbstractWe describe here our Machine Translation (MT) model and the results we obtained for the IWSLT 2017 Multilingual Shared Task. Motivated by Zero Shot NMT [1] we trained a Multilingual …...

In this paper we explore the utility of Machine Translation as a writing aid and its impact on the quality of the text produced. We focus on medical practitioners who …...

AbstractWe present a memory augmented neural network for natural language understanding: Neural Semantic Encoders. NSE is equipped with a novel memory update rule and has a variable sized encoding memory …...

The field of Quality Estimation (QE) has the goal to provide automatic methods for the evaluation of Machine Translation (MT), that do not require reference transla- tions in their computation. …...

The present paper describes and presents ongoing research on machine translation (MT) and linguistic intercomprehension. One main goal, although not the only one, is to evaluate three machine translation (MT) …...

AbstractOver the last 4 years, Infor has been implementing machine translation (MT) in its translation process. In this paper, the results of both statistical and neural MT projects are provide …...

The need for cross-lingual information access is more than ever with the easy accessibility to the Internet, especially in vastly multilingual societies like India. Cross-lingual summarization can help minimize human …...

AbstractWith the resurgence of chat-based dialog systems in consumer and enterprise applications, there has been much success in developing data-driven and rule-based natural language models to understand human intent. Since …...

AbstractConsiderable effort has been devoted to building commonsense knowledge bases. However, they are not available in many languages because the construction of KBs is expensive. To bridge the gap between …...

The surge of social media use has triggered huge demands of multilingual sentiment anal- ysis (MSA) for various purposes, such as unveiling cultural difference. So far, tradi- tional methods resorted …...

We present an evaluation of the benefits of domain adaptation for machine translation, on three separate domains and language pairs, with varying degrees of domain specificity and amounts of available …...

In this paper, we present evaluation corpora covering four genres for four language pairs that we harvested from the web in an automated fashion. We use these multi-genre benchmarks to …...

AbstractA popular application of machine translation (MT) is gisting: MT is consumed as is to make sense of text in a foreign language. Evaluation of the usefulness of MT for …...

Although measuring intrinsic quality has been a key factor in the advancement of Machine Translation (MT), successfully deploying MT requires considering not just intrinsic quality but also the user experience, …...

AbstractThis study analyzes usage statistics and the results of an end-user survey to compile a snapshot of the current use and users of one online machine translation (MT) tool, Multilizer’s …...

This paper investigates the robustness of NLP against perturbed word forms. While neural approaches can achieve (almost) human-like accuracy for certain tasks and conditions, they often are sensitive to small …...

AbstractTelugu is the fifteenth most commonly spoken language in the world with an estimated reach of 75 million people in the Indian subcontinent. At the same time, it is a …...

AbstractTraditional active learning (AL) methods for machine translation (MT) rely on heuristics. However, these heuristics are limited when the characteristics of the MT problem change due to e.g. the language …...

AbstractWhile systems using the Neural Network-based Machine Translation (NMT) paradigm achieve the highest scores on recent shared tasks, phrase-based (PBMT) systems, rule-based (RBMT) systems and other systems may get better …...

We attempted to generate a sentence by using the concept of core vocabulary whilst preserv- ing the original meaning of the sentence in the text simplification subtask. The correlation between …...

AbstractTranslation memories (TM) and machine translation (MT) both are potentially useful resources for professional translators, but they are often still used independently in translation workflows. As translators tend to have …...

The goal of this work is to design a machine translation (MT) system for a low-resource family of dialects, collectively known as Swiss German, which are widely spoken in Switzerland …...

AbstractWe present mtrain, a convenience tool for machine translation. It wraps existing machine translation libraries and scripts to ease their use. mtrain is written purely in Python 3, well-documented, and …...

AbstractWe describe the first experimental results in neural machine translation for Basque. As a synthetic language featuring agglutinative morphology, an extended case system, complex verbal morphology and relatively free word …...

One of the major challenges in the field of Natural Language Processing (NLP) is the handling of idioms; seemingly ordinary phrases which could be further conjugated or even spread across …...

AbstractGiven (i) the rise of a new paradigm to machine translation based on neural networks that results in more fluent and less literal output than previous models and (ii) the …...

Smart solutions and solid solutions are two different approaches for computational linguistics. To receive a satisfactory result at a minimum cost, smart solutions use special properties of the on-hand application. …...

AbstractThe advances of deep learning approaches in automatic speech recognition (ASR) and machine translation (MT) have allowed for levels of accuracy that move speech translation closer to being a commercially …...

AbstractWebTerm Connector is a plugin for STAR MT Translate which combines machine translation with validated terminology information. The aim is to provide “understandable” information in the target language using corporate …...

In this paper, we present two resources that were created as part of the Multi Arabic Dialect Applications and Resources (MADAR) project. The first is a large parallel corpus of …...

AbstractThis short presentation introduces ModernMT: an open-source project 1 that integrates real-time adaptive neural machine translation into a single easy-to-use product....

AbstractMachine Translation (MT) already plays an important part in software development process at McAfee where the technology can be leveraged to provide early builds for localization and internationalization testing teams. …...

AbstractThe overall machine translation quality available for professional translators working with the Spanish–Basque pair is rather poor, which is a deterrent for its adoption. This work investigates the plausibility of …...

In several areas of NLP evaluation, test suites have been used to analyze the strengths and weaknesses of systems. Today, Machine Translation (MT) quality is usually assessed by shallow automatic …...

AbstractTranslation Quality Estimation (QE) aims to estimate the quality of an automated machine translation (MT) output without any human intervention or reference translation. With the increasing use of MT systems …...

There are many machine translation (MT) papers that propose novel approaches and show improvements over their self-defined baselines. The experimental setting in each paper often differs from one another. As …...

AbstractA spoken language translation (ST) system consists of at least two modules: an automatic speech recognition (ASR) system and a machine translation (MT) system. In most cases, an MT is …...

A major issue in machine translation (MT) applications is the recognition and translation of named entities. This is especially true for Chinese and Japanese, whose scripts present linguistic and algorithmic …...

WordNet-like resources are lexical databases with highly relevance information and data which could be exploited in more complex computational linguistics research and applications. The building process requires manual and automatic …...

AbstractGlobally normalized neural sequence models are considered superior to their locally normalized equivalents because they may ameliorate the effects of label bias. However, when considering high-capacity neural parametrizations that condition …...

AbstractSelf-attention networks (SAN) have attracted a lot of interests due to their high parallelization and strong performance on a variety of NLP tasks, e.g. machine translation. Due to the lack …...

AbstractIn this work, we investigate the possibility of using fully automatic text simplification system on the English source in machine translation (MT) for improving its translation into an under-resourced language. …...

AbstractSemantic role labeling (SRL) is an important task for understanding natural languages, where the objective is to analyse propositions expressed by the verb and to identify each word that bears …...

AbstractIn a pipeline speech translation system, automatic speech recognition (ASR) system will transmit errors in recognition to the downstream machine translation (MT) system. A standard machine translation system is usually …...

AbstractCompositional generalization is a basic mechanism in human language learning, but current neural networks lack such ability. In this paper, we conduct fundamental research for encoding compositionality in neural networks. …...

AbstractFor automatic speech translation (AST), end-to-end approaches are outperformed by cascaded models that transcribe with automatic speech recognition (ASR), then trans- late with machine translation (MT). A major cause of …...

AbstractLexically-constrained sequence decoding allows for explicit positive or negative phrase-based constraints to be placed on target output strings in generation tasks such as machine translation or monolingual text rewriting. We …...

Two of the more predominant technologies that professional translators have at their disposal for improving productivity are machine translation (MT) and computer- aided translation (CAT) tools based on translation memories …...

AbstractThe state of the art in machine translation (MT) is governed by neural approaches, which typically provide superior translation accuracy over statistical approaches. However, on the closely related task of …...

AbstractWe introduce the Scratchpad Mechanism, a novel addition to the sequence-to-sequence (seq2seq) neural network architecture and demonstrate its effectiveness in improving the overall fluency of seq2seq models for natural language …...

AbstractIn many machine learning scenarios, supervision by gold labels is not available and conse quently neural models cannot be trained directly by maximum likelihood estimation. In a weak supervision scenario, …...

AbstractMost machine translation systems generate text autoregressively from left to right. We, instead, use a masked language modeling objective to train a model to predict any subset of the target …...

AbstractIt is challenging to deploy deep neural nets on memory-constrained devices due to the explosion of numbers of parameters. Especially, the input embedding layer and Softmax layer usually dominate the …...

AbstractPronouns are often dropped in Chinese sentences, and this happens more frequently in conversational genres as their referents can be easily understood from context. Recovering dropped pronouns is essential to …...

The goal of cross-lingual information re- trieval (CLIR) is to find relevant docu- ments written in languages different from that of the query. Robustness to transla- tion errors is one …...

AbstractResidual has been widely applied to build deep neural networks with enhanced feature propagation and improved accuracy. In the literature, multiple variants of residual structure are proposed. However, most of …...

AbstractFor machine translation, a vast majority of language pairs in the world are considered low-resource because they have little parallel data available. Besides the technical challenges of learning with limited …...

AbstractWe present an approach for recursively splitting and rephrasing complex English sentences into a novel semantic hierarchy of simplified sentences, with each of them presenting a more regular structure that …...

AbstractApplications such as machine translation, speech recognition, and information retrieval require efficient handling of noun compounds as they are one of the possible sources for out of vocabulary words. In-depth …...

AbstractCorpus-based approaches to machine translation (MT) have difficulties when the amount of parallel corpora to use for training is scarce, especially if the languages involved in the translation are highly …...

AbstractWe present a resource for computational experiments on Mapudungun, a polysynthetic indigenous language spoken in Chile with upwards of 200 thousand speakers. We provide 142 hours of culturally significant conversations …...

AbstractOne critical issue of zero anaphora resolution (ZAR) is the scarcity of labeled data. This study explores how effectively this problem can be alleviated by data augmentation. We adopt a …...

AbstractTypically, tokenization is the very first step in most text processing works. As a token serves as an atomic unit that embeds the contextual information of text, how to define …...

AbstractPredicting the quality of machine translation has traditionally been addressed with language-specific models, under the assumption that the quality label distribution or linguistic features exhibit traits that are not shared …...

AbstractSEBAMAT (semantics-based MT) is a Marie Curie project intended to con-tribute to the state of the art in machine translation (MT). Current MT systems typically take the semantics of a …...

AbstractRecent machine translation shared tasks have shown top-performing systems to tie or in some cases even outperform human translation. Such conclusions about system and human performance are, however, based on …...

AbstractThis paper shows the utility of two open-source tools designed for parallel data cleaning: Bifixer and Bicleaner. Already used to clean highly noisy parallel content from crawled multilingual websites, we …...

AbstractIn this paper, we propose a new task of machine translation (MT), which is based on no parallel sentences but can refer to a ground-truth bilingual dictionary. Motivated by the …...

AbstractIn automatic speech translation (ST), traditional cascade approaches involving separate transcription and translation steps are giving ground to increasingly competitive and more robust direct solutions. In particular, by translating speech …...

AbstractHuman translators often resort to different non-literal translation techniques besides the literal translation, such as idiom equivalence, generalization, particularization, semantic modulation, etc., especially when the source and target languages have …...

AbstractThis article describes the results of a workshop in which 50 translators tested two experimental translation interfaces, as part of a project which aimed at studying the details of editing …...

AbstractWe conducted a survey to understand the impact of machine translation and post-editing awareness on comprehension of and trust in messages disseminated to prepare the public for a weather-related crisis, …...

AbstractSequence-to-sequence learning involves a trade-off between signal strength and annotation cost of training data. For example, machine translation data range from costly expert-generated translations that enable supervised learning, to weak …...

AbstractDocument-level (doc-level) human eval-uation of machine translation (MT) has raised interest in the community after a fewattempts have disproved claims of “human parity” (Toral et al., 2018; Laubli et al.,2018). …...

AbstractWhile state-of-the-art models that rely upon massively multilingual pretrained encoders achieve sample efficiency in downstream applications, they still require abundant amounts of unlabelled text. Nevertheless, most of the world’s languages …...

AbstractWe present FELIX – a flexible text-editing approach for generation, designed to derive maximum benefit from the ideas of decoding with bi-directional contexts and self-supervised pretraining. In contrast to conventional …...

AbstractMachine translation systems perform reasonably well when the input is well-formed speech or text. Conversational speech is spontaneous and inherently consists of many disfluencies. Producing fluent translations of disfluent source …...

AbstractIn this paper we present a pipeline developed at Acolad to test a Machine Translation (MT) engine and compute the discount to be applied when its output is used in …...

AbstractTranslationese is a phenomenon present in human translations, simultaneous interpreting, and even machine translations. Some translationese features tend to appear in simultaneous interpreting with higher frequency than in human text …...

AbstractThe ability of machine translation (MT) models to correctly place markup is crucial to generating high-quality translations of formatted input. This paper compares two commonly used methods of representing markup …...

AbstractDeep neural models tremendously improved machine translation. In this context, we investigate whether distinguishing machine from human translations is still feasible. We trained and applied 18 classifiers under two settings: …...

AbstractRecent studies have demonstrated the effectiveness of cross-lingual language model pre-training on different NLP tasks, such as natural language inference and machine translation. In our work, we test this approach …...

AbstractIn the literature, the research on abstract meaning representation (AMR) parsing is much restricted by the size of human-curated dataset which is critical to build an AMR parser with good …...

AbstractNeural network based models have achieved impressive results on the sentence classification task. However, most of previous work focuses on designing more sophisticated network or effective learning paradigms on monolingual …...

AbstractIt has been conjectured that multilingual information can help monolingual word sense disambiguation (WSD). However, existing WSD systems rarely consider multilingual information, and no effective method has been proposed for …...

AbstractConditional masked language model (CMLM) training has proven successful for non-autoregressive and semi-autoregressive sequence generation tasks, such as machine translation. Given a trained CMLM, however, it is not clear what …...

AbstractIn this paper, we describe Dell EMC’s framework to automatically collect MT-related productivity metrics from a large translation supply chain over an extended period of time, the characteristics and volume …...

Research on providing machine translation systems for unseen language pairs is gaining increasing attention in recent years. However, the quality of their systems is poor for most language pairs, especially …...

AbstractCode-mixing is a phenomenon which arises mainly in multilingual societies. Multilingual people, who are well versed in their native languages and also English speakers, tend to code-mix using English-based phonetic …...

AbstractMachine Translation (MT) is a sub-field of Artificial Intelligence and Natural Language Processing that investigates and studies the ways of automatically translating a text from one language to another. In …...

AbstractThe attention mechanism is the crucial component of the transformer architecture. Recent research shows that most attention heads are not confident in their decisions and can be pruned. However, removing …...

AbstractMachine translation provides powerful methods to convert text between languages, and is therefore a technology enabling a multilingual world. An important part of communication, however, takes place at the non-propositional …...

Adapting machine translation systems in the real world is a difficult problem. In contrast to offline training, users cannot provide the type of fine-grained feedback (such as correct translations) typically …...

AbstractWe propose a family of metrics to assess language generation derived from population estimation methods widely used in ecology. More specifically, we use mark-recapture and maximum-likelihood methods that have been …...

AbstractData privacy is an important issue for “machine learning as a service” providers. We focus on the problem of membership inference attacks: Given a data sample and black-box access to …...

AbstractWhen translating “The secretary asked for details.” to a language with grammatical gender, it might be necessary to determine the gender of the subject “secretary”. If the sentence does not …...

AbstractQuestion answering (QA) models have shown rapid progress enabled by the availability of large, high-quality benchmark datasets. Such annotated datasets are difficult and costly to collect, and rarely exist in …...

AbstractThis paper presents a user evaluation of machine translation and post-editing for TV subtitles. Based on a process study where 12 professional subtitlers translated and post-edited subtitles, we compare effort …...

AbstractIn this paper, we present a machine translation system implemented by the Translation Centre for the Bodies of the European Union (CdT). The main goal of this project is to …...

AbstractIn this paper, we demonstrate our machine translation system applied for the Chinese-Japanese bidirectional translation task (aka. open domain translation task) for the IWSLT 2020. Our model is based on …...

AbstractIn this paper we demonstrate our (OPPO’s) machine translation systems for the WMT20 Shared Task on News Translation for all the 22 language pairs. We will give an overview of …...

AbstractThis paper presents OPUS-MT a project that focuses on the development of free resources and tools for machine translation. The current status is a repository of over 1,000 pre-trained neural …...

AbstractResearch in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. ‘Low-resourced’-ness is a complex problem going …...

AbstractApproaches to Quality Estimation (QE) of machine translation have shown promising results at predicting quality scores for translated sentences. However, QE models are often trained on noisy approximations of quality …...

AbstractWe believe that machine translation (MT) must be introduced to translation students as part of their training, in preparation for their professional life. In this paper we present a new …...

AbstractUnsupervised neural machine translation (UNMT) has recently attracted great interest in the machine translation community. The main advantage of the UNMT lies in its easy collection of required large training …...

AbstractThis paper describes the acquisition, preprocessing and characteristics of SEDAR, a large scale English-French parallel corpus for the financial domain. Our extensive experiments on machine translation show that SEDAR is …...

AbstractLabel smoothing has been shown to be an effective regularization strategy in classification, that prevents overfitting and helps in label de-noising. However, extending such methods directly to seq2seq settings, such …...

AbstractWe propose a novel method of automatic sentence alignment from noisy parallel documents. We first formalize the sentence alignment problem as the independent predictions of spans in the target document …...

AbstractThis report summarizes the Air Force Research Laboratory (AFRL) machine translation (MT) systems submitted to the news-translation task as part of the 2020 Conference on Machine Translation (WMT20) evaluation campaign. …...

AbstractThis paper presents the key results of a study on the global competitiveness of the European Language Technology market for three areas – Machine Translation, speech technology, and cross-lingual search. …...

Sentiment classification has been crucial for many natural language processing (NLP) applica- tions, such as the analysis of movie reviews, tweets, or customer feedback. A sufficiently large amount of data …...

AbstractThis paper surveys the first, three-year phase of a project at the National Research Council of Canada that is developing software to assist Indigenous communities in Canada in preserving their …...

The issue of preservation and revitalization of the indigenous languages is gaining attention from the public in recent days. Developing NLP techniques related to the indigenous languages will help to …...

AbstractDubbing has two shades; synchronisation constraints are applied only when the actor’s mouth is visible on screen, while the translation is unconstrained for off-screen dubbing. Consequently, different synchronisation requirements, and …...

AbstractThe Sumerian cuneiform script was invented more than 5,000 years ago and represents one of the oldest in history. We present the first attempt to translate Sumerian texts into English …...

AbstractIn this paper we propose a unified approach for supporting different generation manners of machine translation, including autoregressive, semi-autoregressive, and refinement-based non-autoregressive models. Our approach works by repeatedly selecting positions …...

AbstractBoth human and machine translation play a central role in cross-lingual transfer learning: many multilingual datasets have been created through professional translation services, and using machine translation to translate either …...

AbstractUnderstanding neural models is a major topic of interest in the deep learning community. In this paper, we propose to interpret a general neural model comparatively. Specifically, we study the …...

AbstractRST-based discourse parsing is an important NLP task with numerous downstream applications, such as summarization, machine translation and opinion mining. In this paper, we demonstrate a simple, yet highly accurate …...

AbstractWord alignment and machine translation are two closely related tasks. Neural translation models, such as RNN-based and Transformer models, employ a target-to-source attention mechanism which can provide rough word alignments, …...

AbstractThe scarcity of parallel data is a major obstacle for training high-quality machine translation systems for low-resource languages. Fortunately, some low-resource languages are linguistically related or similar to high-resource languages; …...

AbstractAutomatic post-editing (APE) models are usedto correct machine translation (MT) system outputs by learning from human post-editing patterns. We present the system used in our submission to the WMT’21 Automatic …...

AbstractExisting approaches for machine translation (MT) mostly translate given text in the source language into the target language and without explicitly referring to information indispensable for producing proper translation. This …...

AbstractWe present BERTGen, a novel, generative, decoder-only model which extends BERT by fusing multimodal and multilingual pre-trained models VL-BERT and M-BERT, respectively. BERTGen is auto-regressively trained for language generation tasks, …...

AbstractWe show that margin-based bitext mining in a multilingual sentence space can be successfully scaled to operate on monolingual corpora of billions of sentences. We use 32 snapshots of a …...

AbstractAdversarial attacks alter NLP model predictions by perturbing test-time inputs. However, it is much less understood whether, and how, predictions can be manipulated with small, concealed changes to the training …...

AbstractDocument machine translation aims to translate the source sentence into the target language in the presence of additional contextual information. However, it typically suffers from a lack of doc-level bilingual …...

AbstractLexical disambiguation is a major challenge for machine translation systems, especially if some senses of a word are trained less often than others. Identifying patterns of overgeneralization requires evaluation methods …...

AbstractFine-grained control of machine translation (MT) outputs along multiple attributes is critical for many modern MT applications and is a requirement for gaining users’ trust. A standard approach for exerting …...

AbstractNatural language generation (NLG) tasks on pro-drop languages are known to suffer from zero pronoun (ZP) problems, and the problems remain challenging due to the scarcity of ZP-annotated NLG corpora. …...

AbstractThis paper proposes an approach to cross-language sentence selection in a low-resource setting. It uses data augmentation and negative sampling techniques on noisy parallel sentence data to directly learn a …...

AbstractRecent pretrained vision-language models have achieved impressive performance on cross-modal retrieval tasks in English. Their success, however, heavily depends on the availability of many annotated image-caption datasets for pretraining, where …...

AbstractRecent progress in task-oriented neural dialogue systems is largely focused on a handful of languages, as annotation of training data is tedious and expensive. Machine translation has been used to …...

In Natural Language Understanding (NLU), to facilitate Cross-Lingual Transfer Learning (CLTL), especially CLTL between distant lan- guages, we integrate CLTL with Machine Translation (MT), and thereby propose a novel CLTL …...

AbstractHuman gender bias is reflected in language and text production. Because state-of-the-art machine translation (MT) systems are trained on large corpora of text, mostly generated by humans, gender bias can …...

AbstractSteedman (2020) proposes as a formal universal of natural language grammar that grammatical permutations of the kind that have given rise to transformational rules are limited to a class known …...

AbstractThe lack of publicly available evaluation data for low-resource languages limits progress in Spoken Language Understanding (SLU). As key tasks like intent classification and slot filling require abundant training data, …...

AbstractDocument-level MT models are still far from satisfactory. Existing work extend translation unit from single sentence to multiple sentences. However, study shows that when we further enlarge the translation unit …...

AbstractEncoder-decoder models have been commonly used for many tasks such as machine translation and response generation. As previous research reported, these models suffer from generating redundant repetition. In this research, …...

AbstractInteractive-predictive translation is a collaborative iterative process and where human translators produce translations with the help of machine translation (MT) systems interactively. Various sampling techniques in active learning (AL) exist …...

AbstractSequence-to-sequence transduction is the core problem in language processing applications as diverse as semantic parsing, machine translation, and instruction following. The neural network models that provide the dominant solution to …...

AbstractReinforcement learning has been proved to be effective in handling low resource machine trans-lation tasks and different sampling methods of reinforcement learning affect the performance ofthe model. The reward for …...

AbstractRecurrent Neural Networks (RNN) have been widely used in various Natural Language Processing (NLP) tasks such as text classification, sequence tagging, and machine translation. Long Short Term Memory (LSTM), a …...

AbstractMultilingual T5 pretrains a sequence-to-sequence model on massive monolingual texts, which has shown promising results on many cross-lingual tasks. In this paper, we improve multilingual text-to-text transfer Transformer with translation …...

AbstractNon-autoregressive generation (NAG) has recently attracted great attention due to its fast inference speed. However, the generation quality of existing NAG models still lags behind their autoregressive counterparts. In this …...

AbstractRecent studies argue that knowledge distillation is promising for speech translation (ST) using end-to-end models. In this work, we investigate the effect of knowledge distillation with a cascade ST using …...

AbstractMachine translation is generally understood as generating one target text from an input source document. In this paper, we consider a stronger requirement: to jointly generate two texts so that …...

AbstractIn Machine Translation, assessing the quality of a large amount of automatic translations can be challenging. Automatic metrics are not reliable when it comes to high performing systems. In addition, …...

AbstractThis paper addresses the efficiency challenge of Neural Architecture Search (NAS) by formulating the task as a ranking problem. Previous methods require numerous training examples to estimate the accurate performance …...

AbstractWe demonstrate that transformers obtain impressive performance even when some of the layers are randomly initialized and never updated. Inspired by old and well-established ideas in machine learning, we explore …...

AbstractMachine translation models have discrete vocabularies and commonly use subword segmentation techniques to achieve an ‘open vocabulary.’ This approach relies on consistent and correct underlying unicode sequences, and makes models …...

AbstractMachine Translation (MT) systems often fail to preserve different stylistic and pragmatic properties of the source text (e.g. sentiment and emotion and gender traits and etc.) to the target and …...

AbstractThe explosion of user-generated content (UGC)—e.g. social media posts and comments and and reviews—has motivated the development of NLP applications tailored to these types of informal texts. Prevalent among these …...

Since traditional tokenizers are isolated from a downstream task and model, they cannot out- put an appropriate tokenization depending on the task and model, although recent studies im- ply that …...