Improving Statistical Machine Translation Efficiency by Triangulation
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Construction of English-Bodo Parallel Text
International Journal on Natural Language Computing (IJNLC) Vol.7, No.5, October 2018 CONSTRUCTION OF ENGLISH -BODO PARALLEL TEXT CORPUS FOR STATISTICAL MACHINE TRANSLATION Saiful Islam 1, Abhijit Paul 2, Bipul Syam Purkayastha 3 and Ismail Hussain 4 1,2,3 Department of Computer Science, Assam University, Silchar, India 4Department of Bodo, Gauhati University, Guwahati, India ABSTRACT Corpus is a large collection of homogeneous and authentic written texts (or speech) of a particular natural language which exists in machine readable form. The scope of the corpus is endless in Computational Linguistics and Natural Language Processing (NLP). Parallel corpus is a very useful resource for most of the applications of NLP, especially for Statistical Machine Translation (SMT). The SMT is the most popular approach of Machine Translation (MT) nowadays and it can produce high quality translation result based on huge amount of aligned parallel text corpora in both the source and target languages. Although Bodo is a recognized natural language of India and co-official languages of Assam, still the machine readable information of Bodo language is very low. Therefore, to expand the computerized information of the language, English to Bodo SMT system has been developed. But this paper mainly focuses on building English-Bodo parallel text corpora to implement the English to Bodo SMT system using Phrase-Based SMT approach. We have designed an E-BPTC (English-Bodo Parallel Text Corpus) creator tool and have been constructed General and Newspaper domains English-Bodo parallel text corpora. Finally, the quality of the constructed parallel text corpora has been tested using two evaluation techniques in the SMT system. -
Usage of IT Terminology in Corpus Linguistics Mavlonova Mavluda Davurovna
International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8, Issue-7S, May 2019 Usage of IT Terminology in Corpus Linguistics Mavlonova Mavluda Davurovna At this period corpora were used in semantics and related Abstract: Corpus linguistic will be the one of latest and fast field. At this period corpus linguistics was not commonly method for teaching and learning of different languages. used, no computers were used. Corpus linguistic history Proposed article can provide the corpus linguistic introduction were opposed by Noam Chomsky. Now a day’s modern and give the general overview about the linguistic team of corpus. corpus linguistic was formed from English work context and Article described about the corpus, novelties and corpus are associated in the following field. Proposed paper can focus on the now it is used in many other languages. Alongside was using the corpus linguistic in IT field. As from research it is corpus linguistic history and this is considered as obvious that corpora will be used as internet and primary data in methodology [Abdumanapovna, 2018]. A landmark is the field of IT. The method of text corpus is the digestive modern corpus linguistic which was publish by Henry approach which can drive the different set of rules to govern the Kucera. natural language from the text in the particular language, it can Corpus linguistic introduce new methods and techniques explore about languages that how it can inter-related with other. for more complete description of modern languages and Hence the corpus linguistic will be automatically drive from the these also provide opportunities to obtain new result with text sources. -
(Meta-) Evaluation of Machine Translation
(Meta-) Evaluation of Machine Translation Chris Callison-Burch Cameron Fordyce Philipp Koehn Johns Hopkins University CELCT University of Edinburgh ccb cs jhu edu fordyce celct it pkoehn inf ed ac uk Christof Monz Josh Schroeder Queen Mary, University of London University of Edinburgh christof dcs qmul ac uk j schroeder ed ac uk Abstract chine translation evaluation workshop. Here we ap- ply eleven different automatic evaluation metrics, This paper evaluates the translation quality and conduct three different types of manual evalu- of machine translation systems for 8 lan- ation. guage pairs: translating French, German, Beyond examining the quality of translations pro- Spanish, and Czech to English and back. duced by various systems, we were interested in ex- We carried out an extensive human evalua- amining the following questions about evaluation tion which allowed us not only to rank the methodologies: How consistent are people when different MT systems, but also to perform they judge translation quality? To what extent do higher-level analysis of the evaluation pro- they agree with other annotators? Can we im- cess. We measured timing and intra- and prove human evaluation? Which automatic evalu- inter-annotator agreement for three types of ation metrics correlate most strongly with human subjective evaluation. We measured the cor- judgments of translation quality? relation of automatic evaluation metrics with This paper is organized as follows: human judgments. This meta-evaluation re- veals surprising facts about the most com- • Section 2 gives an overview of the shared task. monly used methodologies. It describes the training and test data, reviews the baseline system, and lists the groups that 1 Introduction participated in the task. -
Enriching an Explanatory Dictionary with Framenet and Propbank Corpus Examples
Proceedings of eLex 2019 Enriching an Explanatory Dictionary with FrameNet and PropBank Corpus Examples Pēteris Paikens 1, Normunds Grūzītis 2, Laura Rituma 2, Gunta Nešpore 2, Viktors Lipskis 2, Lauma Pretkalniņa2, Andrejs Spektors 2 1 Latvian Information Agency LETA, Marijas street 2, Riga, Latvia 2 Institute of Mathematics and Computer Science, University of Latvia, Raina blvd. 29, Riga, Latvia E-mail: [email protected], [email protected] Abstract This paper describes ongoing work to extend an online dictionary of Latvian – Tezaurs.lv – with representative semantically annotated corpus examples according to the FrameNet and PropBank methodologies and word sense inventories. Tezaurs.lv is one of the largest open lexical resources for Latvian, combining information from more than 300 legacy dictionaries and other sources. The corpus examples are extracted from Latvian FrameNet and PropBank corpora, which are manually annotated parallel subsets of a balanced text corpus of contemporary Latvian. The proposed approach augments traditional lexicographic information with modern cross-lingually interpretable information and enables analysis of word senses from the perspective of frame semantics, which is substantially different from (complementary to) the traditional approach applied in Latvian lexicography. In cases where FrameNet and PropBank corpus evidence aligns well with the word sense split in legacy dictionaries, the frame-semantically annotated corpus examples supplement the word sense information with clarifying usage examples and commonly used semantic valence patterns. However, the annotated corpus examples often provide evidence of a different sense split, which is often more coarse-grained and, thus, may help dictionary users to cluster and comprehend a fine-grained sense split suggested by the legacy sources. -
20 Toward a Sustainable Handling of Interlinear-Glossed Text in Language Documentation
Toward a Sustainable Handling of Interlinear-Glossed Text in Language Documentation JOHANN-MATTIS LIST, Max Planck Institute for the Science of Human History, Germany 20 NATHANIEL A. SIMS, The University of California, Santa Barbara, America ROBERT FORKEL, Max Planck Institute for the Science of Human History, Germany While the amount of digitally available data on the worlds’ languages is steadily increasing, with more and more languages being documented, only a small proportion of the language resources produced are sustain- able. Data reuse is often difficult due to idiosyncratic formats and a negligence of standards that couldhelp to increase the comparability of linguistic data. The sustainability problem is nicely reflected in the current practice of handling interlinear-glossed text, one of the crucial resources produced in language documen- tation. Although large collections of glossed texts have been produced so far, the current practice of data handling makes data reuse difficult. In order to address this problem, we propose a first framework forthe computer-assisted, sustainable handling of interlinear-glossed text resources. Building on recent standardiza- tion proposals for word lists and structural datasets, combined with state-of-the-art methods for automated sequence comparison in historical linguistics, we show how our workflow can be used to lift a collection of interlinear-glossed Qiang texts (an endangered language spoken in Sichuan, China), and how the lifted data can assist linguists in their research. CCS Concepts: • Applied computing → Language translation; Additional Key Words and Phrases: Sino-tibetan, interlinear-glossed text, computer-assisted language com- parison, standardization, qiang ACM Reference format: Johann-Mattis List, Nathaniel A. -
Public Project Presentation and Updates
7.2: Public Project Presentation and Updates Philipp Koehn Distribution: Public EuroMatrix Statistical and Hybrid Machine Translation Between All European Languages IST 034291 Deliverable 7.2 December 21, 2007 Project funded by the European Community under the Sixth Framework Programme for Research and Technological Development. Project ref no. IST-034291 Project acronym EuroMatrix Project full title Statistical and Hybrid Machine Translation Between All Eu- ropean Languages Instrument STREP Thematic Priority Information Society Technologies Start date / duration 01 September 2006 / 30 Months Distribution Public Contractual date of delivery September 1, 2007 Actual date of delivery September 13, 2007 Deliverable number 7.2 Deliverable title Public Project Presentation and Updates Type Report, contractual Status & version Finished Number of pages 19 Contributing WP(s) WP7 WP / Task responsible WP7 / 7.6 Other contributors none Author(s) Philipp Koehn EC project officer Xavier Gros Keywords The partners in EuroMatrix are: Saarland University (USAAR) University of Edinburgh (UEDIN) Charles University (CUNI-MFF) CELCT GROUP Technologies MorphoLogic For copies of reports, updates on project activities and other EuroMatrix-related in- formation, contact: The EuroMatrix Project Co-ordinator Prof. Hans Uszkoreit Universit¨at des Saarlandes, Computerlinguistik Postfach 15 11 50 66041 Saarbr¨ucken, Germany [email protected] Phone +49 (681) 302-4115- Fax +49 (681) 302-4700 Copies of reports and other material can also be accessed via the project’s homepage: http://www.euromatrix.net/ c 2007, The Individual Authors No part of this document may be reproduced or transmitted in any form, or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission from the copyright owner. -
Linguistic Annotation of the Digital Papyrological Corpus: Sematia
Marja Vierros Linguistic Annotation of the Digital Papyrological Corpus: Sematia 1 Introduction: Why to annotate papyri linguistically? Linguists who study historical languages usually find the methods of corpus linguis- tics exceptionally helpful. When the intuitions of native speakers are lacking, as is the case for historical languages, the corpora provide researchers with materials that replaces the intuitions on which the researchers of modern languages can rely. Using large corpora and computers to count and retrieve information also provides empiri- cal back-up from actual language usage. In the case of ancient Greek, the corpus of literary texts (e.g. Thesaurus Linguae Graecae or the Greek and Roman Collection in the Perseus Digital Library) gives information on the Greek language as it was used in lyric poetry, epic, drama, and prose writing; all these literary genres had some artistic aims and therefore do not always describe language as it was used in normal commu- nication. Ancient written texts rarely reflect the everyday language use, let alone speech. However, the corpus of documentary papyri gets close. The writers of the pa- pyri vary between professionally trained scribes and some individuals who had only rudimentary writing skills. The text types also vary from official decrees and orders to small notes and receipts. What they have in common, though, is that they have been written for a specific, current need instead of trying to impress a specific audience. Documentary papyri represent everyday texts, utilitarian prose,1 and in that respect, they provide us a very valuable source of language actually used by common people in everyday circumstances. -
8.14: Annual Public Report
8.14: Annual Public Report S. Busemann, O. Bojar, C. Callison-Burch, M. Cettolo, R. Garabik, J. van Genabith, P. Koehn, H. Schwenk, K. Simov, P. Wolf Distribution: Public EuroMatrixPlus Bringing Machine Translation for European Languages to the User ICT 231720 Deliverable 8.14 Project funded by the European Community under the Seventh Framework Programme for Research and Technological Development. Project ref no. ICT-231720 Project acronym EuroMatrixPlus Project full title Bringing Machine Translation for European Languages to the User Instrument STREP Thematic Priority ICT-2007.2.2 Cognitive systems, interaction, robotics Start date / duration 01 March 2009 / 38 Months Distribution Public Contractual date of delivery November 15, 2011 Actual date of delivery December 05, 2011 Date of last update December 5, 2011 Deliverable number 8.14 Deliverable title Annual Public Report Type Report Status & version Final Number of pages 13 Contributing WP(s) all WP / Task responsible DFKI Other contributors All Participants Author(s) S. Busemann, O. Bojar, C. Callison-Burch, M. Cettolo, R. Garabik, J. van Genabith, P. Koehn, H. Schwenk, K. Simov, P. Wolf EC project officer Michel Brochard Keywords The partners in DFKI GmbH, Saarbr¨ucken (DFKI) EuroMatrixPlus University of Edinburgh (UEDIN) are: Charles University (CUNI-MFF) Johns Hopkins University (JHU) Fondazione Bruno Kessler (FBK) Universit´edu Maine, Le Mans (LeMans) Dublin City University (DCU) Lucy Software and Services GmbH (Lucy) Central and Eastern European Translation, Prague (CEET) Ludovit Stur Institute of Linguistics, Slovak Academy of Sciences (LSIL) Institute of Information and Communication Technologies, Bulgarian Academy of Sciences (IICT-BAS) For copies of reports, updates on project activities and other EuroMatrixPlus-related information, contact: The EuroMatrixPlus Project Co-ordinator Prof. -
Statistical and Hybrid Machine Translation Between All European Languages
Statistical and hybrid machine translation between all European languages Publishable executive summary 01 September 2006 – 30 November 2007 Acronym: EuroMatrix Contract N°: IST 034291 Duration: 30 months from 01/09/2006 Coordinator: Prof. Dr. Hans Uszkoreit Saarland University D-66123 Saarbrücken [email protected] Scientific coordinator: Dr. Philipp Koehn Edinburgh University [email protected] PROJECT FUNDED BY THE EUROPEAN COMMUNITY UNDER THE SIXTH FRAMEWORK PROGRAMME FOR RESEARCH AND TECHNOLOGICAL DEVELOPMENT. Contractors involved Saarland University Germany Computational Linguistics The University of Edinburgh United Kingdom School of Informatics Univerzita Karlova v Praze/ Charles University Prague Czech Republic Institute of Formal and Applied Linguistics CELCT Center for the Evaluation of Language and Italy Communication Technologies MorphoLogic Hungary Germany Group Technologies AG -------------------------------------------------------------------------------------------- Publishable Executive Summary ©The EuroMatrix consortium, 2008 Summary description of project objectives EuroMatrix aims at a major push in machine translation technology applying the most advanced MT technologies systematically to all pairs of EU languages. Special attention is being paid to the languages of the new and near-term prospective member states. As part of this application development, EuroMatrix designs and investigates novel combinations of statistical techniques and linguistic knowledge sources as well as hybrid MT architectures. EuroMatrix addresses urgent European economic and social needs by concentrating on European languages and on high-quality translation to be employed for the publication of technical, social, legal and political documents. EuroMatrix aims at enriching the statistical MT approach with novel learning paradigms and experiment with new combinations of methods and resources from statistical MT, rule-based MT, shallow language processing and computational lexicography/morphology. -
Text and Corpus Analysis: Computer-Assisted Studies of Language and Culture
© Copyright Michael Stubbs 1996. This is chapter 1 of Text and Corpus Analysis which was published by Blackwell in 1996. TEXT AND CORPUS ANALYSIS: COMPUTER-ASSISTED STUDIES OF LANGUAGE AND CULTURE MICHAEL STUBBS CHAPTER 1. TEXTS AND TEXT TYPES Attested language text duly recorded is in the focus of attention for the linguist. (Firth 1957b: 29.) The main question discussed in this book is as follows: How can an analysis of the patterns of words and grammar in a text contribute to an understanding of the meaning of the text? I discuss traditions of text analysis in (mainly) British linguistics, and computer-assisted methods of text and corpus analysis. And I provide analyses of several shorter and longer texts, and also of patterns of language across millions of words of text corpora. The main emphasis is on the analysis of attested, naturally occurring textual data. An exclusive concentration on the text alone is, however, not an adequate basis for text interpretation, and this introductory chapter discusses the appropriate balance for text analysis, between the text itself and its production and reception. Such analyses of attested texts are important for both practical and theoretical reasons, and the main reasons can be easily and briefly stated. First, there are many areas of the everyday world in which the systematic and critical interpretation of texts is an important social skill. One striking example occurs in courtrooms, where very important decisions, by juries as well as lawyers, can depend on such interpretations. Second, much of theoretical linguistics over the past fifty years has been based on the study of isolated sentences. -
Latvian Framenet: Cross-Lingual Issues
96 Human Language Technologies – The Baltic Perspective K. Muischnek and K. Müürisep (Eds.) © 2018 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/978-1-61499-912-6-96 Latvian FrameNet: Cross-Lingual Issues Gunta NESPORE-Bˇ ERZKALNE¯ 1, Baiba SAULITE¯ and Normunds GRUZ¯ ITIS¯ Institute of Mathematics and Computer Science, University of Latvia Abstract. This paper reports the lessons learned while creating a FrameNet- annotated text corpus of Latvian. This is still an ongoing work, a part of a larger project which aims at the creation of a multilayer text corpus, anchored in cross- lingual state-of-the-art representations: Universal Dependencies (UD), FrameNet and PropBank, as well as Abstract Meaning Representation (AMR). For the FrameNet layer, we use the latest frame inventory of Berkeley FrameNet (BFN v1.7), while the annotation itself is done on top of the underlying UD layer. We strictly follow a corpus-driven approach, meaning that lexical units (LU) in Latvian FrameNet are created only based on the annotated corpus examples. Since we are aiming at a medium-sized still general-purpose corpus, an important aspect that we take into account is the variety and balance of the corpus in terms of genres, do- mains and LUs. We have finished the first phase of the FrameNet corpus annota- tion, and we have collected and discuss cross-lingual issues and their possible so- lutions. The issues are relevant for other languages as well, particularly if the goal is to maintain cross-lingual compatibility via BFN. -
Abstract the Circle of Meaning: from Translation
ABSTRACT Title of dissertation: THE CIRCLE OF MEANING: FROM TRANSLATION TO PARAPHRASING AND BACK Nitin Madnani, Doctor of Philosophy, 2010 Dissertation directed by: Professor Bonnie Dorr Department of Computer Science The preservation of meaning between inputs and outputs is perhaps the most ambitious and, often, the most elusive goal of systems that attempt to process natural language. Nowhere is this goal of more obvious importance than for the tasks of machine translation and paraphrase generation. Preserving meaning between the input and the output is paramount for both, the monolingual vs bilingual distinction notwithstanding. In this thesis, I present a novel, symbiotic relationship between these two tasks that I term the “circle of meaning”. Today’s statistical machine translation (SMT) systems require high quality human translations for parameter tuning, in addition to large bi-texts for learning the translation units. This parameter tuning usually involves generating translations at different points in the parameter space and obtaining feedback against human- authored reference translations as to how good the translations. This feedback then dictates what point in the parameter space should be explored next. To measure this feedback, it is generally considered wise to have multiple (usually 4) reference translations to avoid unfair penalization of translation hypotheses which could easily happen given the large number of ways in which a sentence can be translated from one language to another. However, this reliance on multiple reference translations creates a problem since they are labor intensive and expensive to obtain. Therefore, most current MT datasets only contain a single reference. This leads to the problem of reference sparsity—the primary open problem that I address in this dissertation— one that has a serious effect on the SMT parameter tuning process.