Аударма дәлдігі

This paper presents a disambiguation approach for translating non-segmented-Kana into Kanji. The method consists of two steps. In the first step, an input sentence is analyzed morphologically and ambiguous morphemes …...

JANUS is a multi-lingual speech-to- speech translation system designed to facilitate communication between two parties engaged in a spontaneous con- versation in a limited domain. In an attempt to achieve …...

We present a set of algorithms that en- able us to translate natural language sentences by exploiting both a trans- lation memory and a statistical-based translation model. Our results show …...

We present a comparative evaluation of two data-driven models used in translation selec- tion of English-Korean machine translation. La- tent semantic analysis(LSA) and probabilistic latent semantic analysis (PLSA) are applied …...

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 …...

Key phrases are usually among the most information-bearing linguistic structures. Translating them correctly will improve many natural language processing appli- cations. We propose a new framework to mine key phrase …...

This work summarizes a comparison between two ap- proaches to Statistical Machine Translation (SMT), namely Ngram-based and Phrase-based SMT. In both approaches, the translation process is based on bilingual units …...

This paper reports the NTT statistical translation system par- ticipating in the evaluation campaign of IWSLT 2005. The NTT system is based on a phrase translation model and uti- lizes …...

Nowadays, most of the statistical translation systems are based on phrases (i.e. groups of words). We describe a phrase-based system using a modified method for the phrase extraction which deals …...

In this paper, we present a novel global re- ordering model that can be incorporated into standard phrase-based statistical ma- chine translation. Unlike previous local reordering models that emphasize the …...

AbstractThis paper presents a reordering framework for statistical machine translation (SMT) where source-side reorderings are integrated into SMT decoding, allowing for a highly constrained reordered search graph. The monotone search …...

Efficient decoding has been a fundamental problem in machine translation, especially with an integrated language model which is essential for achieving good translation quality. We develop faster approaches for this …...

In this paper, we present a simple and effective method to address the issue of how to generate diversified translation systems from a single Statistical Machine Translation (SMT) engine for …...

Statistical translation models that try to capture the recursive structure of language have been widely adopted over the last few years. These models make use of vary- ing amounts of …...

We present Mixture Model-based Mini- mum Bayes Risk (MMMBR) decoding, an approach that makes use of multiple SMT systems to improve translation ac- curacy. Unlike existing MBR decoding methods defined …...

AbstractA key aspect in the development of statistical translators is the synergic combination of different sources of knowledge. This work describes the effect and implications that would have adding additional …...

This paper presents a study conducted in the course of implementing a project in the World Intellectual Property Organiza- tion (WIPO) on assisted translation of pat- ent abstracts and titles …...

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 …...

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 …...

Incorporating semantic structure into linguistics-free translation model is chal-a lenging, since semantic structures are closely tied to syntax. In this paper, we propose a two-level approach to exploiting predicate-argument structure …...

We present an unsupervised learning model that induces phrasal inversion transduction grammars by introducing a minimum conditional description length (CDL) principle to drive search over a space defined by two …...

We propose a new method for translation ac- quisition which uses a set of synonyms to ac- quire translations from comparable corpora. The motivation is that, given a certain query …...

AbstractKnowledge base (KB) such as Freebase plays an important role for many natural language processing tasks. English knowledge base is obviously larger and of higher quality than low resource language …...

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 …...

AbstractThis paper presents a high-quality multilingual dataset for the documentation domain to advance research on localization of structured text. Unlike widely-used datasets for translation of plain text, we collect XML-structured …...

AbstractDue to the unparallelizable nature of the autoregressive factorization, AutoRegressive Translation (ART) models have to generate tokens sequentially during decoding and thus suffer from high inference latency. Non-AutoRegressive Translation (NART) …...

AbstractPriming is a well known and studied psychology phenomenon based on the prior presentation of one stimulus (cue) to influence the processing of a response. In this paper, we propose …...

Recently, several studies have proposed pre- trained encoder-decoder models using mono- lingual data, such as BART, which can im- prove the accuracy of seq2seq tasks via fine- tuning with task-specific …...

Improving the robustness of neural machine translation models on variations of input sen- tences is an active area of research. In this paper, we propose a simple data augmenta- tion …...

AbstractWe propose a novel technique that combines alternative subword tokenizations of a single source-target language pair that allows us to leverage multilingual neural translation training methods. These alternate segmentations function …...