Proceedings of the COLING 2004 Post Conference Workshop on Multilingual Linguistic Ressources MLR2004

International audienceIn an ever expanding information society, most information systems are now facing the "multilingual challenge". Multilingual language resources play an essential role in modern information systems. Such resources need to provide information on many languages in a common framework and should be (re)usable in many applications (for automatic or human use). Many centres have been involved in national and international projects dedicated to building har- monised language resources and creating expertise in the maintenance and further development of standardised linguistic data. These resources include dictionaries, lexicons, thesauri, word-nets, and annotated corpora developed along the lines of best practices and recommendations. However, since the late 90's, most efforts in scaling up these resources remain the responsibility of the local authorities, usually, with very low funding (if any) and few opportunities for academic recognition of this work. Hence, it is not surprising that many of the resource holders and developers have become reluctant to give free access to the latest versions of their resources, and their actual status is therefore currently rather unclear. The goal of this workshop is to study problems involved in the development, management and reuse of lexical resources in a multilingual context. Moreover, this workshop provides a forum for reviewing the present state of language resources. The workshop is meant to bring to the international community qualitative and quantitative information about the most recent developments in the area of linguistic resources and their use in applications. The impressive number of submissions (38) to this workshop and in other workshops and conferences dedicated to similar topics proves that dealing with multilingual linguistic ressources has become a very hot problem in the Natural Language Processing community. To cope with the number of submissions, the workshop organising committee decided to accept 16 papers from 10 countries based on the reviewers' recommendations. Six of these papers will be presented in a poster session. The papers constitute a representative selection of current trends in research on Multilingual Language Resources, such as multilingual aligned corpora, bilingual and multilingual lexicons, and multilingual speech resources. The papers also represent a characteristic set of approaches to the development of multilingual language resources, such as automatic extraction of information from corpora, combination and re-use of existing resources, online collaborative development of multilingual lexicons, and use of the Web as a multilingual language resource. The development and management of multilingual language resources is a long-term activity in which collaboration among researchers is essential. We hope that this workshop will gather many researchers involved in such developments and will give them the opportunity to discuss, exchange, compare their approaches and strengthen their collaborations in the field. The organisation of this workshop would have been impossible without the hard work of the program committee who managed to provide accurate reviews on time, on a rather tight schedule. We would also like to thank the Coling 2004 organising committee that made this workshop possible. Finally, we hope that this workshop will yield fruitful results for all participants

Domain-specific word embeddings for ICD-9-CM classification

In this work we evaluate domain-speci�c embedding models induced from textual resources in the medical domain. The International Classi�cation of Diseases (ICD) is a standard, broadly used classi�cation system, that codes a large number of speci�c diseases, symptoms, injuries and medical procedures into numerical classes. Assigning a code to a clinical case means classifying that case into one or more particular discrete class, hence allowing further statistics studies and automated calculations. The possibility to have a discrete code instead of a text in natural language is intuitively a great advantage for data processing systems. The use of such classi�cation is becoming increasingly important for, but not limited to, economic and policy-making purposes. Experiments show that domain-speci�c word embeddings, instead of a general one, improves classi�ers in terms of frequency similarities between words

Phraseology in Corpus-based transaltion studies : stylistic study of two contempoarary Chinese translation of Cervantes's Don Quijote

The present work sets out to investigate the stylistic profiles of two modern Chinese versions of Cervantes???s Don Quijote (I): by Yang Jiang (1978), the first direct translation from Castilian to Chinese, and by Liu Jingsheng (1995), which is one of the most commercially successful versions of the Castilian literary classic. This thesis focuses on a detailed linguistic analysis carried out with the help of the latest textual analytical tools, natural language processing applications and statistical packages. The type of linguistic phenomenon singled out for study is four-character expressions (FCEXs), which are a very typical category of Chinese phraseology. The work opens with the creation of a descriptive framework for the annotation of linguistic data extracted from the parallel corpus of Don Quijote. Subsequently, the classified and extracted data are put through several statistical tests. The results of these tests prove to be very revealing regarding the different use of FCEXs in the two Chinese translations. The computational modelling of the linguistic data would seem to indicate that among other findings, while Liu???s use of archaic idioms has followed the general patterns of the original and also of Yang???s work in the first half of Don Quijote I, noticeable variations begin to emerge in the second half of Liu???s more recent version. Such an idiosyncratic use of archaisms by Liu, which may be defined as style shifting or style variation, is then analyzed in quantitative terms through the application of the proposed context-motivated theory (CMT). The results of applying the CMT-derived statistical models show that the detected stylistic variation may well point to the internal consistency of the translator in rendering the second half of Part I of the novel, which reflects his freer, more creative and experimental style of translation. Through the introduction and testing of quantitative research methods adapted from corpus linguistics and textual statistics, this thesis has made a major contribution to methodological innovation in the study of style within the context of corpus-based translation studies.Imperial Users onl

Phraseology in Corpus-Based Translation Studies: A Stylistic Study of Two Contemporary Chinese Translations of Cervantes's Don Quijote

The present work sets out to investigate the stylistic profiles of two modern Chinese versions of Cervantes’s Don Quijote (I): by Yang Jiang (1978), the first direct translation from Castilian to Chinese, and by Liu Jingsheng (1995), which is one of the most commercially successful versions of the Castilian literary classic. This thesis focuses on a detailed linguistic analysis carried out with the help of the latest textual analytical tools, natural language processing applications and statistical packages. The type of linguistic phenomenon singled out for study is four-character expressions (FCEXs), which are a very typical category of Chinese phraseology. The work opens with the creation of a descriptive framework for the annotation of linguistic data extracted from the parallel corpus of Don Quijote. Subsequently, the classified and extracted data are put through several statistical tests. The results of these tests prove to be very revealing regarding the different use of FCEXs in the two Chinese translations. The computational modelling of the linguistic data would seem to indicate that among other findings, while Liu’s use of archaic idioms has followed the general patterns of the original and also of Yang’s work in the first half of Don Quijote I, noticeable variations begin to emerge in the second half of Liu’s more recent version. Such an idiosyncratic use of archaisms by Liu, which may be defined as style shifting or style variation, is then analyzed in quantitative terms through the application of the proposed context-motivated theory (CMT). The results of applying the CMT-derived statistical models show that the detected stylistic variation may well point to the internal consistency of the translator in rendering the second half of Part I of the novel, which reflects his freer, more creative and experimental style of translation. Through the introduction and testing of quantitative research methods adapted from corpus linguistics and textual statistics, this thesis has made a major contribution to methodological innovation in the study of style within the context of corpus-based translation studies

Getting Past the Language Gap: Innovations in Machine Translation

In this chapter, we will be reviewing state of the art machine translation systems, and will discuss innovative methods for machine translation, highlighting the most promising techniques and applications. Machine translation (MT) has benefited from a revitalization in the last 10 years or so, after a period of relatively slow activity. In 2005 the field received a jumpstart when a powerful complete experimental package for building MT systems from scratch became freely available as a result of the unified efforts of the MOSES international consortium. Around the same time, hierarchical methods had been introduced by Chinese researchers, which allowed the introduction and use of syntactic information in translation modeling. Furthermore, the advances in the related field of computational linguistics, making off-the-shelf taggers and parsers readily available, helped give MT an additional boost. Yet there is still more progress to be made. For example, MT will be enhanced greatly when both syntax and semantics are on board: this still presents a major challenge though many advanced research groups are currently pursuing ways to meet this challenge head-on. The next generation of MT will consist of a collection of hybrid systems. It also augurs well for the mobile environment, as we look forward to more advanced and improved technologies that enable the working of Speech-To-Speech machine translation on hand-held devices, i.e. speech recognition and speech synthesis. We review all of these developments and point out in the final section some of the most promising research avenues for the future of MT

A think-aloud protocols investigation of lexico-semantic problems and problem-solving strategies among trainee English-Arabic translators.

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN039294 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Word-to-Word Models of Translational Equivalence

Parallel texts (bitexts) have properties that distinguish them from other kinds of parallel data. First, most words translate to only one other word. Second, bitext correspondence is noisy. This article presents methods for biasing statistical translation models to reflect these properties. Analysis of the expected behavior of these biases in the presence of sparse data predicts that they will result in more accurate models. The prediction is confirmed by evaluation with respect to a gold standard -- translation models that are biased in this fashion are significantly more accurate than a baseline knowledge-poor model. This article also shows how a statistical translation model can take advantage of various kinds of pre-existing knowledge that might be available about particular language pairs. Even the simplest kinds of language-specific knowledge, such as the distinction between content words and function words, is shown to reliably boost translation model performance on some tasks. Statistical models that are informed by pre-existing knowledge about the model domain combine the best of both the rationalist and empiricist traditions