2022/12/08 更新

写真a

ルパージュ イヴ
ルパージュ イヴ
Scopus 論文情報  
論文数: 0  Citation: 0  h-index: 6

Citation Countは当該年に発表した論文の被引用数

所属
理工学術院 大学院情報生産システム研究科
職名
教授

学内研究所・附属機関兼任歴

  • 2020年
    -
    2022年

    理工学術院総合研究所   兼任研究員

学歴

  •  
    -
    1985年

    フランス国立グルノブル大学   情報学研究科   情報学 自然言語処理  

  •  
    -
    1983年

    Mines Saint-Etienne フランス グランドぜコール   工学研究科   情報学  

所属学協会

  •  
     
     

    情報処理学会

  •  
     
     

    ATALA フランス自然言語処理学会

  •  
     
     

    自然言語処理学会

  •  
     
     

    フランス自然言語処理雑誌編集委員会

 

研究分野

  • 知能情報学

  • 言語学

研究キーワード

  • 自動翻訳、多言語アラインメント、類推関係、言い換え、言語モデル、外国語ソフト

論文

  • Improving automatic Chinese-Japanese patent translation using bilingual term extraction

    Wei Yang, Yves Lepage

    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING   13 ( 1 ) 117 - 125  2018年01月  [査読有り]

     概要を見る

    The identification of terms in scientific and patent documents is a crucial issue for applications like information retrieval, text categorization, and also for machine translation. This paper describes a method to improve Chinese-Japanese statistical machine translation of patents by re-tokenizing the training corpus with aligned bilingual multi-word terms. We automatically extract multi-word terms from monolingual corpora by combining statistical and linguistic filtering methods. An automatic alignment method is used to identify corresponding terms. The most promising bilingual multi-word terms are extracted by setting some threshold on translation probabilities and further filtering by considering the components of the bilingual multi-word terms in characters as well as the ratio of their lengths in words. We also use kanji (Japanese)-hanzi (Chinese) character conversion to confirm and extract more promising bilingual multi-word terms. We obtain a high quality of correspondence with 93% in bilingual term extraction and a significant improvement of 1.5 BLEU score in a translation experiment. (c) 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

    DOI

    Scopus

    1
    被引用数
    (Scopus)
  • Inflating a small parallel corpus into a large quasi-parallel corpus using monolingual data for Chinese–Iapanese machine translation

    Wei Yang, Hanfei Shen, Yves Lepage

    Journal of Information Processing   25 ( 0 ) 88 - 99  2017年

     概要を見る

    Increasing the size of parallel corpora for less-resourced language pairs is essential for machine translation (MT). To address the shortage of parallel corpora between Chinese and Japanese, we propose a method to construct a quasi-parallel corpus by inflating a small amount of Chinese–Japanese corpus, so as to improve statistical machine translation (SMT) quality. We generate new sentences using analogical associations based on large amounts of monolingual data and a small amount of parallel data. We filter over-generated sentences using two filtering methods: one based on BLEU and the second one based on N-sequences. We add the obtained aligned quasi-parallel corpus to a small parallel Chinese–Japanese corpus and perform SMT experiments. We obtain significant improvements over a baseline system.

    DOI CiNii

    Scopus

    2
    被引用数
    (Scopus)
  • Inflating a small parallel corpus into a large quasi-parallel corpus using monolingual data for Chinese–Iapanese machine translation

    Yang, Wei, Shen, Hanfei, Lepage, Yves

    Journal of Information Processing   25   88 - 99  2017年

     概要を見る

    © 2017 Information Processing Society of Japan.Increasing the size of parallel corpora for less-resourced language pairs is essential for machine translation (MT). To address the shortage of parallel corpora between Chinese and Japanese, we propose a method to construct a quasi-parallel corpus by inflating a small amount of Chinese–Japanese corpus, so as to improve statistical machine translation (SMT) quality. We generate new sentences using analogical associations based on large amounts of monolingual data and a small amount of parallel data. We filter over-generated sentences using two filtering methods: one based on BLEU and the second one based on N-sequences. We add the obtained aligned quasi-parallel corpus to a small parallel Chinese–Japanese corpus and perform SMT experiments. We obtain significant improvements over a baseline system.

    DOI

    Scopus

    2
    被引用数
    (Scopus)
  • A method of generating translations of unseen n-grams by using proportional analogy

    Juan Luo, Yves Lepage

    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING   11 ( 3 ) 325 - 330  2016年05月  [査読有り]

     概要を見る

    In recent years, statistical machine translation has gained much attention. The phrase-based statistical machine translation model has made significant advancement in translation quality over the word-based model. In this paper, we attempt to apply the technique of proportional analogy to statistical machine translation systems. We propose a novel approach to apply proportional analogy to generate translations of unseen n-grams from the phrase table for phrase-based statistical machine translation. Experiments are conducted with two datasets of different sizes. We also investigate two methods to integrate n-grams translations produced by proportional analogy into the state-of-the-art statistical machine translation system, Moses.(1) The experimental results show that unseen n-grams translations generated using the technique of proportional analogy are rewarding for statistical machine translation systems with small datasets. (c) 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

    DOI

    Scopus

    1
    被引用数
    (Scopus)
  • Morphological predictability of unseen words using computational analogy

    Fam, Rashel, Lepage, Yves

    CEUR Workshop Proceedings   1815   51 - 60  2016年01月

     概要を見る

    Copyright © 2016 for this paper by its authors.We address the problem of predicting unseen words by relying on the organization of the vocabulary of a language as exhibited by paradigm tables. We present a pipeline to automatically produce paradigm tables from all the words contained in a text. We measure how many unseen words from an unseen test text can be predicted using the paradigm tables obtained from a training text. Experiments are carried out in several languages to compare the morphological richness of languages, and also the richness of the vocabulary of different authors.

  • Solving analogical equations between strings of symbols using neural networks

    Kaveeta, Vivatchai, Lepage, Yves

    CEUR Workshop Proceedings   1815   67 - 76  2016年01月

     概要を見る

    Copyright © 2016 for this paper by its authors.A neural network model to solve analogical equations between strings of symbols is proposed. The method transforms the input strings into two fixed size alignment matrices. The matrices act as the input of the neural network which predicts two output matrices. Finally, a string decoder transforms the predicted matrices into the final string output. By design, the neural network is constrained by several properties of analogy. The experimental results show a fast learning rate with a high prediction accuracy that can beat a baseline algorithm.

  • HSSA tree structures for BTG-based preordering in machine translation

    Zhang, Yujia, Zhang, Yujia, Wang, Hao, Lepage, Yves

    Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation, PACLIC 2016     123 - 132  2016年01月

     概要を見る

    The Hierarchical Sub-Sentential Alignment (HSSA) method is a method to obtain aligned binary tree structures for two aligned sentences in translation correspondence. We propose to use the binary aligned tree structures delivered by this method as training data for preordering prior to machine translation. For that, we learn a Bracketing Transduction Grammar (BTG) from these binary aligned tree structures. In two oracle experiments in English to Japanese and Japanese to English translation, we show that it is theoretically possible to outperform a baseline system with a default distortion limit of 6, by about 2.5 and 5 BLEU points and, 7 and 10 RIBES points respectively, when preordering the source sentences using the learnt preordering model and using a distortion limit of 0. An attempt at learning a preordering model and its results are also reported.

  • Yet another symmetrical & real-time word alignment method: Hierarchical sub-sentential alignment using F-measure

    Wang, Hao, Lepage, Yves

    Proceedings of the 30th Pacific Asia Conference on Language, Information and Computation, PACLIC 2016     143 - 152  2016年01月

     概要を見る

    Symmetrization of word alignments is the fundamental issue in statistical machine translation (SMT). In this paper, we describe an novel reformulation of Hierarchical Subsentential Alignment (HSSA) method using F-measure. Starting with a soft alignment matrix, we use the F-measure to recursively split ENGL the matrix into two soft alignment submatrices. A direction is chosen as the same time on the basis of Inversion Transduction Grammar (ITG). In other words, our method simplifies the processing of word alignment as recursive segmentation in a bipartite graph, which is simple and easy to implement. It can be considered as an alternative of growdiag- final-and heuristic. We show its application on phrase-based SMT systems combined with the state-of-the-art approaches. In addition, by feeding with word-to-word associations, it also can be a real-time word aligner. Our experiments show that, given a reliable lexicon translation table, this simple method can yield comparable results with state-of-theart approaches.

  • Extraction of Potentially Useful Phrase Pairs for Statistical Machine Translation

    Juan Luo, Yves Lepage

    Journal of Information Processing   23 ( 3 ) 344 - 352  2015年

     概要を見る

    Over the last decade, an increasing amount of work has been done to advance the phrase-based statistical machine translation model in which the method of extracting phrase pairs consists of word alignment and phrase extraction. In this paper, we show that, for Japanese-English and Chinese-English statistical machine translation systems, this method is indeed missing potentially useful phrase pairs which could lead to better translation scores. These potentially useful phrase pairs can be detected by looking at the segmentation traces after decoding. We choose to see the problem of extracting potentially useful phrase pairs as a two-class classification problem: among all the possible phrase pairs, distinguish the useful ones from the not-useful ones. As for any classification problem, the question is to discover the relevant features which contribute the most. Extracting potentially useful phrase pairs resulted in a statistically significant improvement of 7.65 BLEU points in English-Chinese and 7.61 BLEU points in Chinese-English experiments. A slight increase of 0.94 BLEU points and 0.4 BLEU points is also observed for English-Japanese system and Japanese-English system, respectively.

    DOI CiNii

    Scopus

    1
    被引用数
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  • Translation of unseen bigrams by analogy using an SVM classifier

    Wang, Hao, Lyu, Lu, Lepage, Yves

    29th Pacific Asia Conference on Language, Information and Computation, PACLIC 2015     16 - 25  2015年01月

     概要を見る

    Detecting language divergences and predicting possible sub-translations is one of the most essential issues in machine translation. Since the existence of translation divergences, it is impractical to straightforward translate from source sentence into target sentence while keeping the high degree of accuracy and without additional information. In this paper, we investigate the problem from an emerging and special point of view: bigrams and the corresponding translations. We first profile corpora and explore the constituents of bigrams in the source language. Then we translate unseen bigrams based on proportional analogy and filter the outputs using an Support Vector Machine (SVM) classifier. The experiment results also show that even a small set of features from analogous can provide meaningful information in translating by analogy.

  • Chinese word segmentation based on analogy and majority voting

    Zheng, Zongrong, Wang, Yi, Lepage, Yves

    29th Pacific Asia Conference on Language, Information and Computation, PACLIC 2015     151 - 156  2015年01月

     概要を見る

    This paper proposes a new method of Chinese word segmentation based on proportional analogy and majority voting. First, we introduce an analogy-based method for solving the word segmentation problem. Second, we show how to use majority voting to make the decision on where to segment. The preliminary results show that this approach compares well with other segmenters reported in previous studies. As an important and original feature, our method does not need any pretraining or lexical knowledge.

  • Analogies Between Binary Images: Application to Chinese Characters

    Yves Lepage

    COMPUTATIONAL APPROACHES TO ANALOGICAL REASONING: CURRENT TRENDS   548   25 - 57  2014年  [査読有り]

     概要を見る

    The purpose of this chapter is to show how it is possible to efficiently extract the structure of a set of objects by use of the notion of proportional analogy. As a proportional analogy involves four objects, the very naive approach to the problem, has basically a complexity of O(n(4)) for a given set of n objects. We show, under some conditions on proportional analogy, how to reduce this complexity to O(n(2)) by considering an equivalent problem, that of enumerating analogical clusters that are informative and not redundant. We further show how some improvements make the task tractable. We illustrate our technique with a task related with natural language processing, that of clustering Chinese characters. In this way, we re-discover the graphical structure of these characters.

    DOI

    Scopus

    9
    被引用数
    (Scopus)
  • Inflating a Training Corpus for SMT by Using Unrelated Unaligned Monolingual Data

    Wei Yang, Yves Lepage

    Advances in Natural Language Processing   8686   236 - 248  2014年  [査読有り]

     概要を見る

    To improve the translation quality of less resourced language pairs, the most natural answer is to build larger and larger aligned training data, that is to make those language pairs well resourced. But aligned data is not always easy to collect. In contrast, monolingual data are usually easier to access. In this paper we show how to leverage unrelated unaligned monolingual data to construct additional training data that varies only a little from the original training data. We measure the contribution of such additional data to translation quality. We report an experiment between Chinese and Japanese where we use 70,000 sentences of unrelated unaligned monolingual additional data in each language to construct new sentence pairs that are not perfectly aligned. We add these sentence pairs to a training corpus of 110,000 sentence pairs, and report an increase of 6 BLEU points.

  • Improved Chinese-Japanese Phrase-based MT Quality Using an Extended Quasi-parallel Corpus

    Hao Wang, Wei Yang, Yves Lepage

    PROCEEDINGS OF 2014 IEEE INTERNATIONAL CONFERENCE ON PROGRESS IN INFORMATICS AND COMPUTING (PIC)     6 - 10  2014年  [査読有り]

     概要を見る

    State-of-the-art phrase-based machine translation (MT) systems usually demand large parallel corpora in the step of training. The quality and the quantity of the training data exert a direct influence on the performance of such translation systems. The lack of open-source bilingual corpora for a particular language pair results in lower translation scores reported for such a language pair. This is the case of Chinese-Japanese. In this paper, we propose to build an extension of an initial parallel corpus in the form of quasi-parallel sentences, instead of adding new parallel sentences. The extension of the initial corpus is obtained by using monolingual analogical associations. Our experiments show that the use of such quasi-parallel corpora improves the performance of Chinese-Japanese translation systems.

    DOI

    Scopus

  • Improving the Distribution of N-Grams in Phrase Tables Obtained by the Sampling-Based Method

    Juan Luo, Adrien Lardilleux, Yves Lepage

    HUMAN LANGUAGE TECHNOLOGY CHALLENGES FOR COMPUTER SCIENCE AND LINGUISTICS   8387   419 - 431  2014年  [査読有り]

     概要を見る

    We describe an approach to improve the performance of sampling-based sub-sentential alignment method on translation tasks by investigating the distribution of n-grams in the phrase tables. This approach consists in enforcing the alignment of n-grams. We compare the quality of phrase translation tables output by this approach and that of the state-of-the-art estimation approach in statistical machine translation tasks. We report significant improvements for this approach and show that merging phrase tables outperforms the state-of-the-art techniques.

    DOI

    Scopus

  • Marker-Based Chunking in Eleven European Languages for Analogy-Based Translation

    Kota Takeya, Yves Lepage

    HUMAN LANGUAGE TECHNOLOGY CHALLENGES FOR COMPUTER SCIENCE AND LINGUISTICS   8387   432 - 444  2014年  [査読有り]

     概要を見る

    An example-based machine translation (EBMT) system based on proportional analogies requires numerous proportional analogies between linguistic units to work properly. Consequently, long sentences cannot be handled directly in such a framework. Cutting sentences into chunks would be a solution. Using different markers, we count the number of proportional analogies between chunks in 11 European languages. As expected, the number of proportional analogies between chunks found is very high. These results, and preliminary experiments in translation, are promising for the EBMT system that we intend to build.

    DOI

    Scopus

  • Analogy-based machine translation using secability

    Tatsuya Kimura, Jin Matsuoka, Yusuke Nishikawa, Yves Lepage

    2014 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI), VOL 2   2   297 - 298  2014年  [査読有り]

     概要を見る

    The problem of reordering remains the main problem in machine translation. Computing structures of sentences and the alignment of substructures is a way that has been proposed to solve this problem. We use secability to compute structures and show its effectiveness in an example-based machine translation.

    DOI

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    1
    被引用数
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  • Generalizing sampling-based multilingual alignment

    Adrien Lardilleux, François Yvon, Yves Lepage

    Machine Translation   27 ( 1 ) 1 - 23  2013年03月

     概要を見る

    Sub-sentential alignment is the process by which multi-word translation units are extracted from sentence-aligned multilingual parallel texts. This process is required, for instance, in the course of training statistical machine translation systems. Standard approaches typically rely on the estimation of several probabilistic models of increasing complexity and on the use of various heuristics, that make it possible to align, first isolated words, then, by extension, groups of words. In this paper, we explore an alternative approach which relies on a much simpler principle: the comparison of occurrence profiles in sub-corpora obtained by sampling. After analyzing the strengths and weaknesses of this approach, we show how to improve the detection of multi-word translation units and evaluate these improvements on machine translation tasks. © 2012 Springer Science+Business Media B.V.

    DOI

    Scopus

    3
    被引用数
    (Scopus)
  • Exploiting parallel corpus for handling out-of-vocabulary words

    Luo, Juan, Tinsley, John, Lepage, Yves

    27th Pacific Asia Conference on Language, Information, and Computation, PACLIC 27     399 - 408  2013年01月

     概要を見る

    © 2013 by Juan Luo, John Tinsley, and Yves Lepage.This paper presents a hybrid model for handling out-of-vocabulary words in Japanese to- English statistical machine translation output by exploiting parallel corpus. As the Japanese writing system makes use of four different script sets (kanji, hiragana, katakana, and romaji), we treat these scripts differently. A machine transliteration model is built to transliterate out-of vocabulary Japanese katakana words into English words. A Japanese dependency structure analyzer is employed to tackle out of-vocabulary kanji and hiragana words. The evaluation results demonstrate that it is an effective approach for addressing out-of vocabulary word problems and decreasing the OOVs rate in the Japanese-to-English machine translation tasks.

  • Can word segmentation be considered harmful for statistical machine translation tasks between Japanese and Chinese?

    Sun, Jing, Sun, Jing, Sun, Jing, Lepage, Yves, Lepage, Yves, Lepage, Yves

    Proceedings of the 26th Pacific Asia Conference on Language, Information and Computation, PACLIC 2012     351 - 360  2012年12月

     概要を見る

    Unlike most Western languages, there are no typographic boundaries between words in written Japanese and Chinese. Word segmentation is thus normally adopted as an initial step in most natural language processing tasks for these Asian languages. Although word segmentation techniques have improved greatly both theoretically and practically, there still remains some problems to be tackled. In this paper, we present an effective approach in extracting Chinese and Japanese phrases without conducting word segmentation beforehand, using a sampling-based multilingual alignment method. According to our experiments, it is also feasible to train a statistical machine translation system on a small Japanese-Chinese training corpus without performing word segmentation beforehand. © 2012 The PACLIC.

  • Hierarchical sub-sentential alignment with anymalign

    Lardilleux, Adrien, Yvon, François, Lepage, Yves

    Proceedings of the 16th Annual Conference of the European Association for Machine Translation, EAMT 2012     279 - 286  2012年01月

     概要を見る

    © 2012 European Association for Machine Translation.We present a sub-sentential alignment algorithm that relies on association scores between words or phrases. This algorithm is inspired by previous work on alignment by recursive binary segmentation and on document clustering. We evaluate the resulting alignments on machine translation tasks and show that we can obtain state-of-the-art results, with gains up to more than 4 BLEU points compared to previous work, with a method that is simple, independent of the size of the corpus to be aligned, and directly computes symmetric alignments. This work also provides new insights regarding the use of "heuristic" alignment scores in statistical machine translation.

  • Improving sampling-based alignment by investigating the distribution of N-grams in phrase translation tables

    Luo, Juan, Lardilleux, Adrien, Lepage, Yves

    PACLIC 25 - Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation     150 - 159  2011年12月

     概要を見る

    This paper describes an approach to improve the performance of sampling-based multilingual alignment on translation tasks by investigating the distribution of n-grams in the translation tables. This approach consists in enforcing the alignment of n-grams. The quality of phrase translation tables output by this approach and that of MGIZA++ is compared in statistical machine translation tasks. Significant improvements for this approach are reported. In addition, merging translation tables is shown to outperform state-of-the-art techniques. © 2011 by Juan Luo, Adrien Lardilleux, and Yves Lepage.

  • Fully-automatic marker-based chunking in 11 European languages and counts of the number of analogies between chunks

    Takeya, Kota, Lepage, Yves

    PACLIC 25 - Proceedings of the 25th Pacific Asia Conference on Language, Information and Computation     567 - 576  2011年12月

     概要を見る

    Analogy has been proposed as a possible principle for example-based machine translation. For such a framework to work properly, the training data should contain a large number of analogies between sentences. Consequently, such a framework can only work properly with short and repetitive sentences. To handle longer and more varied sentences, cutting the sentences into chunks could be a solution if the number of analogies between chunks is confirmed to be large. This paper thus reports counts of number of analogies using different numbers of chunk markers in 11 European languages. These experiments confirm that the number of analogies between chunks is very large: several tens of thousands of analogies between chunks extracted from sentences among which only very few analogies, if not none, were found. © 2011 by Kota Takeya and Yves Lepage.

  • Estimating the proximity between languages by their commonality in vocabulary structures

    Yves Lepage, Julien Gosme, Adrien Lardilleux

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   6562   127 - 138  2011年

     概要を見る

    This article proposes a possible way of measuring proximity between languages: it consists in measuring the commonality of structures between the vocabularies of two languages. Experiments conducted on a multilingual lexicon of nine European languages acquired from the Acquis communautaire confirmed usual knowledge on the closeness or remoteness of these languages. © 2011 Springer-Verlag.

    DOI

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  • Ambiguity spotting using WordnNet semantic similarity in support to recommended practice for software requirements specifications

    Jin Matsuoka, Yves Lepage

    NLP-KE 2011 - Proceedings of the 7th International Conference on Natural Language Processing and Knowledge Engineering     479 - 484  2011年

     概要を見る

    Word Sense Disambiguation is a crucial problem in documents whose purpose is to serve as specifications for automatic systems. The combination of different techniques of Natural Language Processing can help in this task. In this paper, we show how to detect ambiguous terms in Software Requirements Specifications. And we propose a computer-aided method that signals the reader for possibly ambiguous usage of terms. The method uses compound term measure (C-value), WordNet semantic similarity (WordNet wup-similarity) and a proposed semantic similarity measure between sentences. © 2011 IEEE.

    DOI

    Scopus

    7
    被引用数
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  • The true score of statistical paraphrase generation

    Chevelu, Jonathan, Chevelu, Jonathan, Putois, Ghislain, Lepage, Yves

    Coling 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference   2   144 - 152  2010年12月

     概要を見る

    This article delves into the scoring function of the statistical paraphrase generation model. It presents an algorithm for exact computation and two applicative experiments. The first experiment analyses the behaviour of a statistical paraphrase generation decoder, and raises some issues with the ordering of n-best outputs. The second experiment shows that a major boost of performance can be obtained by embedding a true score computation inside a Monte-Carlo sampling based paraphrase generator.

  • The structure of unseen trigrams and its application to language models: A first investigation

    Yves Lepage, Julien Gosme, Adrien Lardilleux

    2010 4th International Universal Communication Symposium, IUCS 2010 - Proceedings     273 - 280  2010年

     概要を見る

    In a series of preparatory experiments in 4 languages on subsets of the Europarl corpus, we show that a large number of unseen trigrams can be reconstructed by proportional analogy with trigrams having the lowest frequencies. We derive a very simple smoothing scheme from this empirical result and show that it outperforms Good-Turing and Kneser-Ney smoothing schemes on trigrams models in all 11 languages on the common multilingual part of the Europarl corpus, except Finnish. ©2010 IEEE.

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▼全件表示

Misc

  • Inflating a Small Parallel Corpus into a Large Quasi-parallel Corpus Using Monolingual Data for Chinese-Japanese Machine Translation

    Wei Yang, Hanfei Shen, Yves Lepage

    情報処理学会論文誌   58 ( 1 )  2017年01月

     概要を見る

    Increasing the size of parallel corpora for less-resourced language pairs is essential for machine translation (MT). To address the shortage of parallel corpora between Chinese and Japanese, we propose a method to construct a quasi-parallel corpus by inflating a small amount of Chinese-Japanese corpus, so as to improve statistical machine translation (SMT) quality. We generate new sentences using analogical associations based on large amounts of monolingual data and a small amount of parallel data. We filter over-generated sentences using two filtering methods: one based on BLEU and the second one based on N-sequences. We add the obtained aligned quasi-parallel corpus to a small parallel Chinese-Japanese corpus and perform SMT experiments. We obtain significant improvements over a baseline system.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.25(2017) (online)DOI http://dx.doi.org/10.2197/ipsjjip.25.88------------------------------Increasing the size of parallel corpora for less-resourced language pairs is essential for machine translation (MT). To address the shortage of parallel corpora between Chinese and Japanese, we propose a method to construct a quasi-parallel corpus by inflating a small amount of Chinese-Japanese corpus, so as to improve statistical machine translation (SMT) quality. We generate new sentences using analogical associations based on large amounts of monolingual data and a small amount of parallel data. We filter over-generated sentences using two filtering methods: one based on BLEU and the second one based on N-sequences. We add the obtained aligned quasi-parallel corpus to a small parallel Chinese-Japanese corpus and perform SMT experiments. We obtain significant improvements over a baseline system.------------------------------This is a preprint of an article intended for publication Journal ofInformation Processing(JIP). This preprint should not be cited. Thisarticle should be cited as: Journal of Information Processing Vol.25(2017) (online)DOI http://dx.doi.org/10.2197/ipsjjip.25.88------------------------------

    CiNii

受賞

  • 早稲田大学ティーチングアワード(2016年春)

    2016年   早稲田大学  

     概要を見る

    自然言語処理科目

共同研究・競争的資金等の研究課題

  • Natural language processing for academic writing in English

    研究期間:

    2018年04月
    -
    2021年03月
     

     概要を見る

    In the 2nd fiscal year, research was carried out on the use of word embedding models to search for substitute words used for academic writing. Human evaluation has been carried out and results compared to a machine translation system (1 paper at int. conf. with reviewing committee, PACLING 2019).N-grams from ACL-ARC have been extracted and classified into True and False lexical bundles using machine learning models trained on manually checked bundles. 18,000 true lexical bundles have been collected and publicly released (1 paper at int. conf. with reviewing committee, ICACSIS 2019). They are useful for composing fluent academic texts. They are plagiarism-free.Work on using sentence embeddings to search for similar sentences in Abstract sections has been conducted. Similar sentences are presented to non-native writers to help them make correction (1 paper at 言語処理学会第26回年次大会, no reviewing committee)A web site has been set up based on the prototype built in the 1st fiscal year. A part-time research assistant is hired to setup the server, create and administer the website, and design and implement the front end user interface. This website is designed to be able to help researchers to compose their scientific articles. It includes a text drafting pane, automatic translation to English when necessary, dictionary lookup, search of similar words/sentences, text generation and finally plagiarism checking. Currently only interface is provided, the main engines will be linked in the future.Some improvements have been made to the research on searching similar words and sentences, and also collection of plagiarism-free lexical bundles. A website has been built and will be put on running when the text generation part is ready.In the third fiscal year, main focus will be on the text generation part. Following the current research trend, deep learning will be applied to generate new text based on the the original text, collection of lexical bundles and the ACL-ARC knowledge base.The text generation engine must be able to combine possible chunks, lexical bundles, discursive and argumentative connectors from already published articles besides conserving the original meaning of the text. Furthermore, text style must be typical to the sections of a paper, which means that typicality of phrases must be conformed.The final part of the research is concerning plagiarism. Metrics used for plagiarism will be surveyed and algorithms used for detecting plagiarism will be determined

  • Self-explainable and fast-to-train example-based machine translation using neural networks

    研究期間:

    2018年04月
    -
    2021年03月
     

     概要を見る

    After working on the direct approach in the first year, work on the indirect approach in example-based machine translation (EBMT) system was performed in the second fiscal year. A system was implemented. Numerical approaches were introduced in adaptation and retrieval (1 paper at international conference). In addition, it was studied how to merge the direct and the indirect approaches in EBMT by analogy. A model has been proposed. It is not yet been integrated in the final EBMT system. It exploits vector representations of words for monolingual comparison (results from Neural NLP) and sub-sentential alignment for bilingual comparison (results from SMT) (1 paper at a national conference, accepted, to be published in fiscal year 2020). Also, work on sentence representations for retrieval and similarity computation started.Data was collected: because we could not acquire the BTEC corpus, we use data from the Tatoeba corpus. A method to produce semantico-formal analogies between sentences was proposed (1 paper at an international conference). The dataset was publicly released. Preliminary experiments in matrix representations of sentences and resolution of analogies between such representations was conducted. No paper has been published. Also experiments in improving bilingual word embedding mapping were conducted (1 paper published at international conference).To run experiments, we could not buy another DeepLearning Box as planned because the prices of went up. Instead, one graphic card (GPU) was added to the DeepLearning Box already acquired in fiscal year 2018.The planning is basically kept.Work planned for the 2nd year, was normally performed: (1) The use of (a) word vector representations, coming from neural NLP, and the use of (b) sub-sentential alignment, coming from statistical machine translation, was adopted for the monolingual and the bilingual cases. The representation of the correspondence between sentences is made by using similarity matrices. The use of sub-sentential alignment and bilingual word embedding mapping was compared in an experiment. (2) In order to go from formal and crispy analogies to softer and more semantically relevant analogies between sentences, a method to solve semantico-formal analogies between sentences was designed. A resource of semantico-formal analogies in English was produced automatically and was publicly released.Work for the 3rd year was initiated: (1) Study of representations of sentences themselves, by use of matrices (of interpolated points in a word embedding space (original approach) or direct sentence embeddings started and is continued. (2) A set of bilingual analogies between sentences extracted from the Tatoeba corpus has been produced. This dataset will be released.Some work delayed: the work on self-explanation of translations was initially planned for the 3rd fiscal year. It was initiated in the 1st year, but was suspended in the 2nd year. It will resume in the 3rd fiscal year. In addition, integrating the resolution of soft analogies in the EBMT system has been slightly delayed.During the 3rd year, work on the prototype system will continue. The self-explainable functionality for tracing recursive translation of fragments of sentences was addressed in the 2nd year in the model proposed for the indirect approach to example-based machine translation. A first interface has been designed. However, work on the visualisation of the traces is needed because traces need to shorter and more readable for the user. Also explanation of how similar retrieved sentences match the sentence to be translated need to be inspected.One of the main work will be to conduct experiments to measure to what extent crispy vs. soft comparison of words in the translation of shorter vs. longer sentences using more dense vs. less dense corpora are more efficient. For that, data should be prepared. Work on sentence representations and representations of the correspondence between sentences will continue. Training times will also be measured and compared with training times in the neural approach to machine translation.Work will be conducted on retrieval of similar sentences. It is a necessary component in an example-based machine translation system. The use of vector representations of sentences and cosine similarity will be compared with more classical methods using suffix arrays and pattern-matching techniques.Work on self-explanation will also resume. Interfaces for the visualisation of traces will be improved. The existing explanations need to be shorter and more easily understandable by a standard user

  • 言語生産性:有効な類推関係クラスターの迅速な抽出・統計的機械翻訳でその評価

    研究期間:

    2015年04月
    -
    2018年03月
     

     概要を見る

    本研究の目的は、1。単言語データから類推関係クラスターを構築し、2。そのクラスターから擬似パラレルコーパスを生成し、3。パラレルコーパスに追加することにより4。統計的機械翻訳(SMT)の精度を向上させる。そのため、様々なツールを実装し公開した。新しいデータ構造も導入した:類推関係グリッド。形態的に貧しい言語を始め形態豊かな言語を渡って様々な言語でデータを構築した:欧州連合の11ヶ国語、中国語、日本語、また追加言語(アラビア語、グルジア語、ナバホ語、ロシア語、トルコ語)。データの一部分は公開した。行った実験で擬似パラレルコーパスの追加により日中SMTの翻訳精度を向上することを明らかにした

  • 統計・用例機械翻訳のためのアラインメント向上と多言語文法パターン公開

    研究期間:

    2011年04月
    -
    2014年03月
     

     概要を見る

    従来機械翻訳システムの翻訳知識は翻訳テーブルにある。翻訳テーブルとは、二カ国語辞書に似たようなものであり、通常の辞書より長い見出しを持ち、その見出しの確率等を表す数値をも含めるものである。翻訳テーブルは文部分的アライナーというツールにより自動的に生成される。本研究では先行研究で提案した文部分的アライナー手法の向上ができた。以前より長い見出しを出力し、特定の場合では最高技術水準の翻訳品質を得られることを示した。また、出力された翻訳テーブルを一部公開した:Europarlバージョン3の11カ国語の共通部分の全言語対を様々な実験設定で得られた翻訳テーブルである

  • アラビア語のマルチメディアプラトフォーム

    研究期間:

    2009年
    -
    2012年
     

学内研究費(特定課題)

  • 統計的機械翻訳システムの開発時間の減少:サンプリング手法の検討

    2015年  

     概要を見る

    Background: to train a statistical machine translation (SMT) system is time-consuming.  In 2013, for the probabilistic approach, a fast alignment method (Fast_align) has been proposed. It is 10 times as fast as the standard method (GIZA++).Goal: the present research project addressed the problem of reducing the training time of SMT systems for the associative approach 1/ in word-to-word associations (Anymalign) and 2/ in hierarchical sub-sentential alignment (Cutnalign), while increasing translation accuracy.Method: 1/ for word-to-word association, we studied two improvements in sampling: a/ sampling given the knowledge of a test set to produce ad-hoc translation tables. Two different techniques to estimate inverse translation probabilities have been studied; b/ relying on whether a word is a hapax or not to build and sample sub-corpora. 2/ For sub-sentential alignment, we accelerated decisions in segmentation and reduced the search space. Core components have been re-implemented in C and we introduced multi-processing.Results: we report improvements in time and translation accuracy using three different language pairs: Spanish-Portuguese, French-English and Finnish-English. Compared to our previous methods, our improved methods increased translation accuracy by one confidence interval in average. Compared with Fast_align, same or lower training times yield similar translation accuracy in the two easiest language pairs.

  • 機械翻訳のための言語生産性の検討:類推関係マップ

    2014年  

     概要を見る

    言語データの構造化の一般的な問題と機械翻訳でその言語データ構造化の結果に基づき翻訳品質改善の問題を扱った。ここでいう構造化とは、類推関係に基づいた構造化のことである。今まで適応した日中データ以外、欧州連合言語に適応するため、加速が必要であった。5倍以上の加速ができ、時間と素性数の様々な値で測定し英仏データで実験最中である。国際会議PolTALにも国内会議言語処理学会年次大会にも発表した日中翻訳実験で本研究で開発したプログラムを適応した。国際ワークショップCogalex2014に発表された論文の実験でも同プログラムを使用した。

  • 用例機械翻訳のための二カ国語の同時構造分析の手法の検討

    2013年  

     概要を見る

    背景と目標 本研究では本研究室で開発している用例翻訳エンジンの適切な翻訳テーブルの検討をする目的である。現在統計翻訳手法の研究が盛んでありのに対して、類推関係に基づく用例翻訳エンジンを開発している。基本技術としては三つの文の部分から4つ目の計算ができる形式化と実装に取り組んでいる(例:「風邪を」:「ひどい風邪が」::「熱さを」:x => x = 「ひどい熱さが」)。統計翻訳後術と同様に翻訳知識として翻訳テーブルが必要である。 翻訳テーブルを生成するため、本研究では単語間アラインメント結果に基づき、(Zha et al., 2001)のクラスタリング手法を適用し、対訳文を同時に構造解析とアラインメントを行なう。構造解析とアラインメントから自動的に翻訳テーブルを生成する。また、以前に提案された単言語構造解析の可切性(secability)手法で得られた翻訳テーブルと比較し、翻訳品質を測定した。本研究の主な結果は次のようになる。 ① 類推関係に基づく用例翻訳エンジンで長文の翻訳の可能性を示した。可切性を利用し、単言語の構造解析を行って、翻訳実験結果で長い文の翻訳は提案手法で可能であると示した。尺度BLEUで測定した翻訳本質は統計翻訳システムより低いが、文の長さの影響を計ると同じグラフの振る舞いの観察ができた。 ② 複数の言語対で実験を行ない、得られた翻訳テーブルを公開した。Europarlコーパスを使用し、予備実験で代表言語対の間で翻訳実験を行なった:フランス語・英語、スペイン語・ポルトガル語、フィンランド語・英語。また、可切性手法で全ての11カ国語の言語対の間の翻訳テーブルを生成し、その翻訳テーブルとそれを使用して得られたBLEUスコアを本研究室のウェッブサイトで公開した(http://133.9.48.109/index/analogy-based-ebmt/、Experiments with an in-house analogy-based EBMT systemを参照)。 ③ 二カ国語同時構造解析アラインメントツールの向上した。一般と特別計算場合の区別によって基礎演算数量を減少し、50倍の加速ができ、マルチプロセッシングを使用し、コア数の半倍弱の加速できて、会わせて4コアで100倍の加速できた。 行なった実験では二カ国語同時構造解析アラインメントで得られた翻訳結果は可切性で得られた結果の比較するとやや低い。しかし、両実験で入力文の構造解析手法は可切性手法であるため、ある意味で不公平な比較となると考えられる。今後の課題として、同時構造解析アラインメントを利用するとき、入力文構造解析を行なわずに翻訳手法の検討をするべき。研究費の使い方: ① 国内と国際学会参加費:Lepage (LTC 2013, ポーランド) 木村竜矢 (AISE 2013, タイ),西川裕介と尾美圭亮 (言語処理学会第20次年大会、札幌) ② 国内と国際学会出張費:木村竜矢 (AISE 2013, タイ),西川裕介と尾美圭亮 (言語処理学会第20次年大会、札幌) ③ 予定した図書購入は研究費の調整のため異なる研究費で購入した。

  • 用例自動翻訳エンジンと実験応用基盤

    2010年  

     概要を見る

    The final goal of this study is to produce an example-based machine translation engine that can be distributed to the research community on a site dedicated to example-based approaches to machine translation. The engine should use chunks to translate by analogy, and should be made fast by using C implementations of basic computations (resolution of analogical equations). The approach should be tested on various data, like the Europarl data.1. Work on chunking has been done by implementing two methods: marker-based chunking (Gough and Way, 2004) (255 lines of Python code for chunking) and secability (Chenon, 2005) (170 lines of Python code).Tests on the Europarl corpus and informal assessment of the relevance of the chunks produced by the two methods has led to prefer the marker-based chunking technique.In contrast to the standard method proposed by (Gough and Way, 2004), we automatically determine the markers as the most frequent less informative words in a corpus (207 lines of Python code).The number of markers can be freely chosen by the user.In contrast to the standard method proposed by (Gough and Way, 2004), we automatically determine whether to cut on the left or on the right of the markers to have a truly language-independent method.There are still problems on this part of the computation, which is currently done by estimating the difference in entropies on the left and right of each marker.Improvements are under study.1.1. We conducted experiments to compute the number of analogies between the chunks obtained (100,000 lines in 11 languages of the Europarl corpus, average sentence length in English: 30 words).This led to a paper at the Japanese Natural Language Processing Annual Conference (gengosyorigakkai) this year.My participation to gengosyorigakkai was charged on this budget.1.2. The production of all chunks for each of the 11 languages of the Europarl corpus (300,000 lines in each language) has been done.The alignment of chunks by computation of lexical weights is currently being done.The corresponding programs have been written and tested (136 lines of code in Python).We determine the most reliable chunk segmentation between two languages by keeping the same average number of chunks for each sentence over the entire corpus.We are currently in the phase of producing the data.1.3. Relatively to language models, trigrams and analogy, a connex research will be reported at the French Natural Language Processing Annual Conference on a new smoothing scheme for trigrams. This technique has been shown to beat even Kneser-Ney smoothing on relatively small amounts of corpora: 300,000 lines from the Europarl corpus in all 11 languages except Finnish.2. The translation engine2.1. A new engine has been reimplemented in Python (511 lines of code).Its main feature is the use of threads. to allow concurrent computation of different kinds.Each of the following task is performed in a different thread:- generation of analogy equations,- resolution of analogical equations,- transfer from source language into target language, and- linking between source text and translation.This allows a clearer design.Work on the design is still in progress.In particular, the use of UML diagrams for class design allowed to improve the code.The engine is now in its 3rd version.Two students are still working on the design of the engine through UML diagrams.Their part-time job salaries charged on this budget.2.2. The resolution of analogical equations as a C library has been integrated within the Python translation engine using C/Python SWIG.The same has been done for the efficient computation of distance or similarity between strings.The use of the C library leads to an acceleration of 5 to 10 times measured on small examples in formal language theory (translation of the context-free language a^n.b^n n into a regular language (ab)^n).3. The validation part of the work is ongoing research.The production of the alignment of chunks in all pairs for the 11 languages of the Europarl corpus is currently being done.The next step will be systematic assessment of translation by analogy of the chunks in each of these pairs using the standard scripts for assessment with various translation quality metrics: WER, BLEU, NIST and TER.4. The disclosure of the translation engine on the example-based web site is unfortunately not yet possible. It is hoped that it is made possible in the next few months.

 

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委員歴

  • 2008年
    -
    2016年

    Reviewing committee of the Traitement automatique des langues (TAL) Journal  Editor-in-chief

  • 2008年
    -
    2016年

    Traitement automatique des langues (TAL) 編集委員会  編集長