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We propose a novel statistical translation model to improve translation selection of collocation. In the statistical approach that has been popularly applied for translation selection, bilingual corpora are used to …...

We address the problem of sentence align- ment for monolingual corpora, a phe- nomenon distinct from alignment in par- allel corpora. Aligning large compara- ble corpora automatically would provide a …...

. 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 …...

This paper introduces a new statistical pre- processing model for Rule-Based Machine Translation (RBMT) systems. We train a Statistical Machine Translation (SMT) system using monolingual corpora. This model can transform …...

AbstractThe Internet is an ever growing source of information stored in documents of different languages. Hence, cross-lingual resources are needed for more and more NLP applications. This paper presents (i) …...

 This paper proposes to use monolingual collocations to improve Statistical Ma- chine Translation (SMT). We make use of the collocation probabilities, which are estimated from monolingual corpora, in two …...

AbstractAutomatic approaches to creating and extending wordnets, which have become very popular in the past decade, inadvertently result in noisy synsets. This is why we propose an approach to detect …...

This paper presents a paraphrase acquisition method that uncovers and exploits generali- ties underlying paraphrases: paraphrase pat- terns are first induced and then used to col- lect novel instances. Unlike …...

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 …...

We estimate the parameters of a phrase- based statistical machine translation sys- tem from monolingual corpora instead of a bilingual parallel corpus. We extend exist- ing research on bilingual lexicon …...

AbstractIn this paper, we describe our generic approach for transferring part-of-speech annotations from a resourced language towards an etymologically closely related non-resourced language, without using any bilingual (i.e., parallel) data. …...

AbstractThe development of linguistic resources for use in natural language processing is of utmost importance for the continued growth of research and development in the field, especially for resource-scarce languages. …...

Statistical phrase-based translation learns translation rules from bilingual corpora, and has traditionally only used monolin- gual evidence to construct features that rescore existing translation candidates. In this work, we present …...

AbstractWe acquire corpora from the domain of independent news from the Tlaxcala website. We build monolingual corpora for 15 languages and parallel corpora for all the combinations of those 15 …...

This article presents a method of training maximum-entropy models to perform lexi- cal selection in a rule-based machine trans- lation system. The training method de- scribed is unsupervised; that is, …...

Vectorial representations of words have grown remarkably popular in natural language process- ing and machine translation. The recent surge in deep learning-inspired methods for producing distributed representations has been widely …...

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 …...

While end-to-end neural machine transla- tion (NMT) has made remarkable progress recently, NMT systems only rely on par- allel corpora for parameter estimation. Since parallel corpora are usually limited in …...

AbstractBilingual lexica are the basis for many cross-lingual natural language processing tasks. Recent works have shown success in learning bilingual dictionary by taking advantages of comparable corpora and a diverse …...

In this paper, we address the task of language- independent, knowledge-lean and unsuper- vised compound splitting, which is an essen- tial component for many natural language pro- cessing tasks such …...

We train a neural machine translation (NMT) system to both translate source- language text and copy target-language text, thereby exploiting monolingual cor- pora in the target language. Specifically, we create …...

AbstractSentence simplification aims to make sentences easier to read and understand. Most recent approaches draw on insights from machine translation to learn simplification rewrites from monolingual corpora of complex and …...

AbstractNeural machine translation (NMT) is a deep learning based approach for machine translation, which yields the state-of-the-art translation performance in scenarios where large-scale parallel corpora are available. Although the high-quality …...

AbstractTo enrich vocabulary of low resource settings, we proposed a novel method which identify loanwords in monolingual corpora. More specifically, we first use cross-lingual word embeddings as the core feature …...

AbstractCognate words, defined as words in different languages which derive from a common etymon, can be useful for language learners, who can leverage the orthographical similarity of cognates to more …...

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 …...

AbstractNon-autoregressive (NAR) neural machine translation is usually done via knowledge distillation from an autoregressive (AR) model. Under this framework, we leverage large monolingual corpora to improve the NAR model’s performance, …...

AbstractIn this paper, we introduce NLP resources for 11 major Indian languages from two major language families. These resources include: (a) large-scale sentence-level monolingual corpora, (b) pre-trained word embeddings, (c) …...

AbstractIn natural language processing, the performance of a semantic similarity task relies heavily on the availability of a large corpus. Various monolingual corpora are available (mainly English); but multilingual resources …...

AbstractWe introduce new monolingual corpora for four indigenous and endangered languages from Peru: Shipibo-konibo, Ashaninka, Yanesha and Yine. Given the total absence of these languages in the web, the extraction …...

AbstractThis review depicts our submission to the WMT20 shared news translation task. WMT is the conference to assess the level of machine translation capabilities of organizations in the word. We …...

AbstractThe Common European Framework of Reference for Languages (CEFR) defines six levels of learner proficiency, and links them to particular communicative abilities. The CEFRLex project aims at compiling lexical resources …...

AbstractIn this work, we present an information-theoretic framework that formulates cross-lingual language model pre-training as maximizing mutual information between multilingual-multi-granularity texts. The unified view helps us to better understand the …...

AbstractUnsupervised machine translation, which utilizes unpaired monolingual corpora as training data, has achieved comparable performance against supervised machine translation. However, it still suffers from data-scarce domains. To address this issue, …...

AbstractBack-translation is a well established approach to improve the performance of Neural Machine Translation (NMT) systems when large monolingual corpora of the target language and domain are available. Recently, diverse …...

AbstractDespite their progress in high-resource language settings, unsupervised bilingual lexicon induction (UBLI) models often fail on corpora with low-resource distant language pairs due to insufficient initialization. In this work, we …...

AbstractIn this paper, we describe our submission to the WMT-2022: Large-Scale Machine Translation Evaluation for African Languages under the Constrained Translation track. We introduce DENTRA, a novel pre-training strategy for …...

AbstractThe zero-shot cross-lingual ability of models pretrained on multilingual and even monolingual corpora has spurred many hypotheses to explain this intriguing empirical result. However, due to the costs of pretraining, …...

AbstractIn this work, we present the work that has been carried on in the MT4All CEF project and the resources that it has generated by leveraging recent research carried out …...

AbstractQuality Estimation (QE) of Machine Translation output suffers from the lack of annotated data to train supervised models across domains and language pairs. In this work, we describe a method …...