Hybrid Strategies. for better products and shorter time-to-market
|
|
|
- Archibald Barnett
- 8 years ago
- Views:
Transcription
1 Hybrid Strategies for better products and shorter time-to-market
2 Background Manufacturer of language technology software & services Spin-off of the research center of Germany/Heidelberg Founded in 1999, located in Heidelberg, Germany Advancement of IBM-technology Logic based Machine Translation Core competence: Machine translation (RBMT) & electronic dictionaries Linguistic text analysis (morphology, syntax, semantics) 2
3 Products 3
4 Products 1 Client- & client/server-solutions translate machine translation product (maintained and developed further since 1996) languages: EN DE, FR DE, (EN FR, ES DE) multi-user versions with user dictionary- & TM-synchronisation translatedict electronic dictionary with innovative search technology IntelliDict (show reading and translation of a word which are best in the context) FlexiFind (find main word in context and display the corresponding dictionary entry) languages: EN DE, FR DE, EN FR, ES DE multi-user version with user dictionary-synchronisation 4
5 Products 2 Server-based solutions Lingenio Translation Server (LTS) for a company s intranet or as a service languages: EN DE, FR DE, (EN FR, ES DE) with user dictionary- & TM-integration, webpage integration Lingenio Dictionary Server (LDS) for a company s intranet or as a service languages: EN DE, FR DE, EN FR, ES DE user dictionary-integration EACL 2014 HyTra - Lingenio
6 Lingenio Translation Server (LTS) Public versions (for testing) itranslate4eu (EU FP7 project) PONS translation portal (partner company PONS GmbH) (preference over bing DE-EN/FR) EACL 2014 HyTra - Lingenio
7 itranslate4eu EACL 2014 HyTra - Lingenio
8 Pons.eu Language Portal EACL 2014 HyTra - Lingenio
9 Lingenio Translation Server Integration via Plug-Ins into Publishing Tools Wordpress,.. CAT-Tools Trados OmegaT, Customization (TMs, user dictionaries) EACL 2014 HyTra - Lingenio
10 Products 3 Text analysis Morphology Syntax (slot grammar analysis) Semantics (shallow semantic structures from slot grammar analyses) Discourse representation (discourse referents, events, referential links) Generation inflected forms & sentences from morphological/syntactic/semantic structures EACL 2014 HyTra - Lingenio
11 Awards 2007: doit Software Award for FlexiDict 2005: doit Software Award for IntelliDict 2000: D2-WAP-Developer Award by Mannesmann Mobilfunk and Nokia for WAP-based Translation Service 1998: European IST-Prize for Talk & Translate 1996: European IST-Prize for Personal Translator EACL 2014 HyTra - Lingenio
12 Quality evaluation Selection 2013: Good network solution (translate pro version12) 2011: Good quality ( translate pro version 12) 2009: Good quality ( translate pro version 11) 2007: Very good quality (translate pro version 11) 2007: Test winner (translate plus version 10) 2005: Good quality (Office dictionary) 2000: Test winner (Personal Translator Office plus) EACL 2014 HyTra - Lingenio
13 Hybrid Strategies Motivation shorter time-to-market with more and better systems Constraints high quality compatibility with rule-based components/systems EACL 2014 HyTra - Lingenio
14 Hybrid Strategies RB-systems Statistical systems/evaluation 1) RB-analysis and -MT information from corpora statistically gained 2) RB-analysis structure-based SMT EACL 2014 HyTra - Lingenio
15 Hybrid Strategies RB-systems Statistical systems/evaluation bootstrapping 1) RB-analysis and -MT information from corpora statistically gained 2) RB-analysis structure-based SMT EACL 2014 HyTra - Lingenio
16 Hybrid Strategies bootstrapping 1) New content for RB-analysis, -MT information from corpora Monolingual learn morphological classification and forms from corpus data learn syntactic information from corpus data learn semantic information from corpus data Multilingual learn dictionary entries from bilingual corpus data EACL 2014 HyTra - Lingenio
17 Hybrid Strategies Monolingual content (for rule-based analysis and MT) learn morphological classification and forms from corpus data Example Deriving de/het gender classification for Dutch nouns for RBMT generation tasks (poster session) learn semantic information from corpus data: semantic typing (using subcategorization & collocation information,..) learn syntactic information from corpus data EACL 2014 HyTra - Lingenio
18 Monolingual Data learn syntactic information from corpus data Strategies: learn grammar rules / parsing MALT-parser (invited talk Joakim Nivre, Nivre et al 2006, Bohnet,..) learn rule selection preferences EACL 2014 HyTra - Lingenio
19 Hybrid Strategies learn grammar rule selection preferences from corpus data use sentence annotations/analyses (stored in database) use alignment and RB-transfer information between analysis nodes (background: slot grammar analyses (dependency grammar) (McCord 1989),.. EACL 2014 HyTra - Lingenio
20 Hybrid Strategies Aumenta la demanda de energía eléctrica por la ola de calor (the demand for electricity increases because of the heat-wave Increase the demand!) EACL 2014 HyTra - Lingenio
21 Hybrid Strategies Example: DE ES improve grammar ES ES: Aumenta la demanda de energía eléctrica por la ola de calor (the demand for electricity increases because of the heat-wave Increase the demand!) DE: Die Nachfrage steigt prefer subj-application to imperative in context. (Babych et al 2012) EACL 2014 HyTra - Lingenio
22 Hybrid Strategies 1.b) Multilingual content for RBMT from corpora learn dictionary entries from bilingual corpus data Autolearn<word> EACL 2014 HyTra - Lingenio
23 Translation Center User dictionaries edition, settings Translation Memories selection, settings Automatic extraction of dictionary entries Postediting: Alternative translations Assistant: Unknown words, Statistics, settings,.. EACL 2014 HyTra - Lingenio
24 AutoLearn<word> extracts suggestions for dictionary entries from postedited MT translation memories from single sentence pairs complete TMs from bilingual text via Lingenio sentence aligner EACL 2014 HyTra - Lingenio
25 AutoLearn<word> bilingual texts European insurance regulation EACL 2014 HyTra - Lingenio
26 AutoLearn<word> align & import into translation memory EACL 2014 HyTra - Lingenio
27 AutoLearn<word> extract from single TM sentences or from complete TMs EACL 2014 HyTra - Lingenio
28 AutoLearn<word> suggestions relate (potentially) to all parts of speech (nouns, verbs, adjectives, ) include multiword expressions can be selected for integration into active user dictionary. EACL 2014 HyTra - Lingenio
29 AutoLearn<word> - Extraction method Use.. 1. Translation relations from system dictionaries 2. Structures as assigned to source and target sentence by the analysis components of the MT system EACL 2014 HyTra - Lingenio
30 Example DE: Die Lithofazien-Analyse der Pliozän-Schicht hat eine gewisse Anzahl von Umweltablagerungen ergeben. EN: Lithofacies analysis of the Pliocene succession unravelled a number of depositional environments. EACL 2014 HyTra - Lingenio
31 Dependency grammar structures EACL 2014 HyTra - Lingenio
32 Dependency grammar structures + transfer knowledge EACL 2014 HyTra - Lingenio
33 Dependency grammar structures + transfer knowledge (+ statistics) EACL 2014 HyTra - Lingenio
34 Dependency grammar structures + transfer knowledge (+ statistics) Derive new relations EACL 2014 HyTra - Lingenio
35 Dependency grammar structures + transfer knowledge (+ statistics) Derive new relations AutoLearn<word> EACL 2014 HyTra - Lingenio
36 Dictionary entries assigned to suggestions make use of morpho-syntactic & semantic information & defaults of the MT system (bootstrapping) Entries can be edited 36
37 Do more! Use analysis constraints! syntactic constraints semantic constraints morphological constraints 37
38 Extended AutoLearn with selection restrictions EACL 2014 HyTra - Lingenio
39 Extended AutoLearn with selection restrictions subject constraint genitive object constraint direct object constraint 39
40 Extended AutoLearn with selection restrictions extract restrictions Lithofazien-Analyse ergibt Anzahl Umweltablagerungen ~ unravel weaken conditions (Lithofazien-Analyse -> Analyse -> Process ) Analyse ergibt Ablagerung Process ergibt Result (frame with less specific words) (frame with semantic types) Select conditions by evaluating occurrences in corpora Analyse/ Process ergibt Ablagerung/ Result ~ unravel, yield? Determine appropriate context items & context type probabilities!
41 Extended AutoLearn soon: version 13 with selection restrictions 41
42 Hybrid Strategies 2) RB-analysis structure-based SMT Basis: slot grammar analysis (McCord 1989),.. abstract dependency structures (shallow semantic representations) database infrastructure a relational database with: Multilingual corpora (Europarl, customer TMs,..) Alignment information Morpho-syntactic, semantic analyses (abstract dependency structures & disambiguations) (Cooperation with University of Stuttgart, SFB 732 (Eckart, Eberle, Heid et al 2010)) Compute translation models on the basis of pairs of such structures
43 RB-analysis structure-based SMT Example: European solvency law EN: The adoption of the Framework Directive at EU level is awaited with anticipation. DE: Mit Spannung wird die Verabschiedung der Rahmenrichtlinie auf EU-Ebene erwartet. EACL 2014 HyTra - Lingenio
44 RB-analysis structure-based SMT EN: The adoption of the Framework Directive at EU level is awaited with anticipation. DE: Mit Spannung wird die Verabschiedung der Rahmenrichtlinie auf EU-Ebene erwartet. Representation of analyses of different type, computed by different systems using different processing parameters, at different times EACL 2014 HyTra - Lingenio
45 RB-analysis structure-based SMT DB-analyses can be displayed as trees (pretty-print facility) EACL 2014 HyTra - Lingenio
46 RB-analysis structure-based SMT dep = abstract dependency structure (shallow semantic structure) different auxiliary structures one event node EACL 2014 HyTra - Lingenio
47 RB-analysis structure-based SMT dep = abstract dependency structure (shallow semantic structure) Source and target structures are more similar structure-based SMT on the basis of abstract dependency analyses better SMT EACL 2014 HyTra - Lingenio
48 Current hybrid developments Lingenio background: Rule-based analysis & translation (DE, EN, ES, FR, ) Investigation of corpora and annotation of corpus segments Different hybrid methods extract mono- and multilingual rules from corpora on the basis of frequency information and annotations determine probabilities for structural and lexical disambiguation decision schemes Compute translation models for structure-based SMT Faster go-to-market, better systems 48
49 Research Improving accuracy and coverage of analysis & translation EU Marie Curie project (Hybrid high quality machine translation) BMWi project FlexNeuroTrans (Flexible MT for medium-sized businesses using neural nets) Hybrid methods, information from the internet for MT,
50 Thank you for your attention! Questions? Contact: ,
Extracting translation relations for humanreadable dictionaries from bilingual text
Extracting translation relations for humanreadable dictionaries from bilingual text Overview 1. Company 2. Translate pro 12.1 and AutoLearn 3. Translation workflow 4. Extraction method 5. Extended
HIERARCHICAL HYBRID TRANSLATION BETWEEN ENGLISH AND GERMAN
HIERARCHICAL HYBRID TRANSLATION BETWEEN ENGLISH AND GERMAN Yu Chen, Andreas Eisele DFKI GmbH, Saarbrücken, Germany May 28, 2010 OUTLINE INTRODUCTION ARCHITECTURE EXPERIMENTS CONCLUSION SMT VS. RBMT [K.
PROMT Technologies for Translation and Big Data
PROMT Technologies for Translation and Big Data Overview and Use Cases Julia Epiphantseva PROMT About PROMT EXPIRIENCED Founded in 1991. One of the world leading machine translation provider DIVERSIFIED
Statistical Machine Translation
Statistical Machine Translation Some of the content of this lecture is taken from previous lectures and presentations given by Philipp Koehn and Andy Way. Dr. Jennifer Foster National Centre for Language
Comprendium Translator System Overview
Comprendium System Overview May 2004 Table of Contents 1. INTRODUCTION...3 2. WHAT IS MACHINE TRANSLATION?...3 3. THE COMPRENDIUM MACHINE TRANSLATION TECHNOLOGY...4 3.1 THE BEST MT TECHNOLOGY IN THE MARKET...4
Integration of Content Optimization Software into the Machine Translation Workflow. Ben Gottesman Acrolinx
Integration of Content Optimization Software into the Machine Translation Workflow Ben Gottesman Acrolinx What is Acrolinx? Acrolinx is Content Optimization Software. It helps authors make their text!
a Chinese-to-Spanish rule-based machine translation
Chinese-to-Spanish rule-based machine translation system Jordi Centelles 1 and Marta R. Costa-jussà 2 1 Centre de Tecnologies i Aplicacions del llenguatge i la Parla (TALP), Universitat Politècnica de
Project Management. From industrial perspective. A. Helle M. Herranz. EXPERT Summer School, 2014. Pangeanic - BI-Europe
Project Management From industrial perspective A. Helle M. Herranz Pangeanic - BI-Europe EXPERT Summer School, 2014 Outline 1 Introduction 2 3 Translation project management without MT Translation project
Overview of MT techniques. Malek Boualem (FT)
Overview of MT techniques Malek Boualem (FT) This section presents an standard overview of general aspects related to machine translation with a description of different techniques: bilingual, transfer,
The SYSTRAN Linguistics Platform: A Software Solution to Manage Multilingual Corporate Knowledge
The SYSTRAN Linguistics Platform: A Software Solution to Manage Multilingual Corporate Knowledge White Paper October 2002 I. Translation and Localization New Challenges Businesses are beginning to encounter
Hybrid Machine Translation Guided by a Rule Based System
Hybrid Machine Translation Guided by a Rule Based System Cristina España-Bonet, Gorka Labaka, Arantza Díaz de Ilarraza, Lluís Màrquez Kepa Sarasola Universitat Politècnica de Catalunya University of the
Module Catalogue for the Bachelor Program in Computational Linguistics at the University of Heidelberg
Module Catalogue for the Bachelor Program in Computational Linguistics at the University of Heidelberg March 1, 2007 The catalogue is organized into sections of (1) obligatory modules ( Basismodule ) that
Translation Solution for
Translation Solution for Case Study Contents PROMT Translation Solution for PayPal Case Study 1 Contents 1 Summary 1 Background for Using MT at PayPal 1 PayPal s Initial Requirements for MT Vendor 2 Business
SYSTRAN Chinese-English and English-Chinese Hybrid Machine Translation Systems for CWMT2011 SYSTRAN 混 合 策 略 汉 英 和 英 汉 机 器 翻 译 系 CWMT2011 技 术 报 告
SYSTRAN Chinese-English and English-Chinese Hybrid Machine Translation Systems for CWMT2011 Jin Yang and Satoshi Enoue SYSTRAN Software, Inc. 4444 Eastgate Mall, Suite 310 San Diego, CA 92121, USA E-mail:
Towards a RB-SMT Hybrid System for Translating Patent Claims Results and Perspectives
Towards a RB-SMT Hybrid System for Translating Patent Claims Results and Perspectives Ramona Enache and Adam Slaski Department of Computer Science and Engineering Chalmers University of Technology and
REALIZATION SORTING ALGORITHM USING PARALLEL TECHNOLOGIES bachelor, Mikhelev Vladimir candidate of Science, prof., Sinyuk Vasily
2. В. Гергель: Современные языки и технологии параллельного программирования. М., Изд-во МГУ, 2012. 3. Синюк, В. Г. Алгоритмы и структуры данных. Белгород: Изд-во БГТУ им. В. Г. Шухова, 2013. REALIZATION
Machine Translation Computer Aided Translation Machine Language Processing
Machine Translation Computer Aided Translation Machine Language Processing Martin Kappus (kapm@zhaw.ch) 1 Machine Translation Computer-Aided Translation Agenda Machine Translation Introduction History
JOB BANK TRANSLATION AUTOMATED TRANSLATION SYSTEM. Table of Contents
JOB BANK TRANSLATION AUTOMATED TRANSLATION SYSTEM Job Bank for Employers Creating a Job Offer Table of Contents Building the Automated Translation System Integration Steps Automated Translation System
M LTO Multilingual On-Line Translation
O non multa, sed multum M LTO Multilingual On-Line Translation MOLTO Consortium FP7-247914 Project summary MOLTO s goal is to develop a set of tools for translating texts between multiple languages in
How the Computer Translates. Svetlana Sokolova President and CEO of PROMT, PhD.
Svetlana Sokolova President and CEO of PROMT, PhD. How the Computer Translates Machine translation is a special field of computer application where almost everyone believes that he/she is a specialist.
Semantic analysis of text and speech
Semantic analysis of text and speech SGN-9206 Signal processing graduate seminar II, Fall 2007 Anssi Klapuri Institute of Signal Processing, Tampere University of Technology, Finland Outline What is semantic
ACCURAT Analysis and Evaluation of Comparable Corpora for Under Resourced Areas of Machine Translation www.accurat-project.eu Project no.
ACCURAT Analysis and Evaluation of Comparable Corpora for Under Resourced Areas of Machine Translation www.accurat-project.eu Project no. 248347 Deliverable D5.4 Report on requirements, implementation
Customizing an English-Korean Machine Translation System for Patent Translation *
Customizing an English-Korean Machine Translation System for Patent Translation * Sung-Kwon Choi, Young-Gil Kim Natural Language Processing Team, Electronics and Telecommunications Research Institute,
PROMT-Adobe Case Study:
For Americas: 330 Townsend St., Suite 117, San Francisco, CA 94107 Tel: (415) 913-7586 Fax: (415) 913-7589 promtamericas@promt.com PROMT-Adobe Case Study: For other regions: 16A Dobrolubova av. ( Arena
Glossary of translation tool types
Glossary of translation tool types Tool type Description French equivalent Active terminology recognition tools Bilingual concordancers Active terminology recognition (ATR) tools automatically analyze
Tibetan-Chinese Bilingual Sentences Alignment Method based on Multiple Features
, pp.273-280 http://dx.doi.org/10.14257/ijdta.2015.8.4.27 Tibetan-Chinese Bilingual Sentences Alignment Method based on Multiple Features Lirong Qiu School of Information Engineering, MinzuUniversity of
A chart generator for the Dutch Alpino grammar
June 10, 2009 Introduction Parsing: determining the grammatical structure of a sentence. Semantics: a parser can build a representation of meaning (semantics) as a side-effect of parsing a sentence. Generation:
Learning Translation Rules from Bilingual English Filipino Corpus
Proceedings of PACLIC 19, the 19 th Asia-Pacific Conference on Language, Information and Computation. Learning Translation s from Bilingual English Filipino Corpus Michelle Wendy Tan, Raymond Joseph Ang,
Special Topics in Computer Science
Special Topics in Computer Science NLP in a Nutshell CS492B Spring Semester 2009 Jong C. Park Computer Science Department Korea Advanced Institute of Science and Technology INTRODUCTION Jong C. Park, CS
Empirical Machine Translation and its Evaluation
Empirical Machine Translation and its Evaluation EAMT Best Thesis Award 2008 Jesús Giménez (Advisor, Lluís Màrquez) Universitat Politècnica de Catalunya May 28, 2010 Empirical Machine Translation Empirical
Word Completion and Prediction in Hebrew
Experiments with Language Models for בס"ד Word Completion and Prediction in Hebrew 1 Yaakov HaCohen-Kerner, Asaf Applebaum, Jacob Bitterman Department of Computer Science Jerusalem College of Technology
Automatic Speech Recognition and Hybrid Machine Translation for High-Quality Closed-Captioning and Subtitling for Video Broadcast
Automatic Speech Recognition and Hybrid Machine Translation for High-Quality Closed-Captioning and Subtitling for Video Broadcast Hassan Sawaf Science Applications International Corporation (SAIC) 7990
Research Assistant in the Research Group: Diversity and Inclusion, Faculty of Human Sciences, University of Potsdam.
Sabrina Gerth Research Group: Diversity and Inclusion Human Sciences Faculty University of Potsdam Karl-Liebknecht-Str. 24-25 D-14476 Potsdam / Golm phone: ++49 (0)331-977-2758 email: sabrina.gerth@uni-potsdam.de
Language and Computation
Language and Computation week 13, Thursday, April 24 Tamás Biró Yale University tamas.biro@yale.edu http://www.birot.hu/courses/2014-lc/ Tamás Biró, Yale U., Language and Computation p. 1 Practical matters
Negation and (finite) verb placement in a Polish-German bilingual child. Christine Dimroth, MPI, Nijmegen
Negation and (finite) verb placement in a Polish-German bilingual child Christine Dimroth, MPI, Nijmegen Consensus: Bilingual L1A bilingual children develop two separate linguistic systems from early on
The history of machine translation in a nutshell
1. Before the computer The history of machine translation in a nutshell 2. The pioneers, 1947-1954 John Hutchins [revised January 2014] It is possible to trace ideas about mechanizing translation processes
Chapter 8. Final Results on Dutch Senseval-2 Test Data
Chapter 8 Final Results on Dutch Senseval-2 Test Data The general idea of testing is to assess how well a given model works and that can only be done properly on data that has not been seen before. Supervised
The English-Swedish-Turkish Parallel Treebank
The English-Swedish-Turkish Parallel Treebank Beáta Megyesi, Bengt Dahlqvist, Éva Á. Csató and Joakim Nivre Department of Linguistics and Philology, Uppsala University first.last@lingfil.uu.se Abstract
An Interactive Hypertextual Environment for MT Training
An Interactive Hypertextual Environment for MT Training Etienne Blanc GETA, CLIPS-IMAG BP 53, F-38041 Grenoble cedex 09 Etienne.Blanc@imag.fr Abstract An interactive hypertextual environment for MT training
Processing: current projects and research at the IXA Group
Natural Language Processing: current projects and research at the IXA Group IXA Research Group on NLP University of the Basque Country Xabier Artola Zubillaga Motivation A language that seeks to survive
Search and Data Mining: Techniques. Text Mining Anya Yarygina Boris Novikov
Search and Data Mining: Techniques Text Mining Anya Yarygina Boris Novikov Introduction Generally used to denote any system that analyzes large quantities of natural language text and detects lexical or
Translating while Parsing
Gábor Prószéky Translating while Parsing Abstract Translations unconsciously rely on the hypothesis that sentences of a certain source language L S can be expressed by sentences of the target language
Sharing resources between free/open-source rule-based machine translation systems: Grammatical Framework and Apertium
Sharing resources between free/open-source rule-based machine translation systems: Grammatical Framework and Apertium Grégoire Détrez, Víctor M. Sánchez-Cartagena, Aarne Ranta gregoire.detrez@gu.se, vmsanchez@prompsit.com,
The TCH Machine Translation System for IWSLT 2008
The TCH Machine Translation System for IWSLT 2008 Haifeng Wang, Hua Wu, Xiaoguang Hu, Zhanyi Liu, Jianfeng Li, Dengjun Ren, Zhengyu Niu Toshiba (China) Research and Development Center 5/F., Tower W2, Oriental
Efficient Techniques for Improved Data Classification and POS Tagging by Monitoring Extraction, Pruning and Updating of Unknown Foreign Words
, pp.290-295 http://dx.doi.org/10.14257/astl.2015.111.55 Efficient Techniques for Improved Data Classification and POS Tagging by Monitoring Extraction, Pruning and Updating of Unknown Foreign Words Irfan
The Principle of Translation Management Systems
The Principle of Translation Management Systems Computer-aided translations with the help of translation memory technology deliver numerous advantages. Nevertheless, many enterprises have not yet or only
4. Clause combining 2
Informática Aplicada a la Traducción Building and Using Translation Memories 4.1 What is a Parall Corpus A Parall Corpus consists of a set of sentences (or other segments of text) in one language, each
LINGSTAT: AN INTERACTIVE, MACHINE-AIDED TRANSLATION SYSTEM*
LINGSTAT: AN INTERACTIVE, MACHINE-AIDED TRANSLATION SYSTEM* Jonathan Yamron, James Baker, Paul Bamberg, Haakon Chevalier, Taiko Dietzel, John Elder, Frank Kampmann, Mark Mandel, Linda Manganaro, Todd Margolis,
Getting Off to a Good Start: Best Practices for Terminology
Getting Off to a Good Start: Best Practices for Terminology Technologies for term bases, term extraction and term checks Angelika Zerfass, zerfass@zaac.de Tools in the Terminology Life Cycle Extraction
Joint efforts to further develop and incorporate Apertium into the document management flow at Universitat Oberta de Catalunya
Joint efforts to further develop and incorporate Apertium into the document management flow at Universitat Oberta de Catalunya Luis Villarejo*, Sergio Ortiz** and Mireia Ginestí** *Learning Technologies
LANGUAGE TRANSLATION SOFTWARE EXECUTIVE SUMMARY Language Translation Software Market Shares and Market Forecasts Language Translation Software Market
LANGUAGE TRANSLATION SOFTWARE EXECUTIVE SUMMARY Language Translation Software Market Shares and Market Forecasts Language Translation Software Market Driving Forces Language Translation Software Cloud
Machine Translation at the European Commission
Directorate-General for Translation Machine Translation at the European Commission Konferenz 10 Jahre Verbmobil Saarbrücken, 16. November 2010 Andreas Eisele Project Manager Machine Translation, ICT Unit
WHITE PAPER. Machine Translation of Language for Safety Information Sharing Systems
WHITE PAPER Machine Translation of Language for Safety Information Sharing Systems September 2004 Disclaimers; Non-Endorsement All data and information in this document are provided as is, without any
Introduction. Philipp Koehn. 28 January 2016
Introduction Philipp Koehn 28 January 2016 Administrativa 1 Class web site: http://www.mt-class.org/jhu/ Tuesdays and Thursdays, 1:30-2:45, Hodson 313 Instructor: Philipp Koehn (with help from Matt Post)
Symbiosis of Evolutionary Techniques and Statistical Natural Language Processing
1 Symbiosis of Evolutionary Techniques and Statistical Natural Language Processing Lourdes Araujo Dpto. Sistemas Informáticos y Programación, Univ. Complutense, Madrid 28040, SPAIN (email: lurdes@sip.ucm.es)
Statistical Machine Translation
Statistical Machine Translation What works and what does not Andreas Maletti Universität Stuttgart maletti@ims.uni-stuttgart.de Stuttgart May 14, 2013 Statistical Machine Translation A. Maletti 1 Main
COMPUTATIONAL DATA ANALYSIS FOR SYNTAX
COLING 82, J. Horeck~ (ed.j North-Holland Publishing Compa~y Academia, 1982 COMPUTATIONAL DATA ANALYSIS FOR SYNTAX Ludmila UhliFova - Zva Nebeska - Jan Kralik Czech Language Institute Czechoslovak Academy
Master of Arts in Linguistics Syllabus
Master of Arts in Linguistics Syllabus Applicants shall hold a Bachelor s degree with Honours of this University or another qualification of equivalent standard from this University or from another university
Automation of Translation: Past, Presence, and Future Karl Heinz Freigang, Universität des Saarlandes, Saarbrücken
Automation of Translation: Past, Presence, and Future Karl Heinz Freigang, Universität des Saarlandes, Saarbrücken Introduction First attempts in "automating" the process of translation between natural
REPORT ON THE WORKBENCH FOR DEVELOPERS
REPORT ON THE WORKBENCH FOR DEVELOPERS for developers DELIVERABLE D3.2 VERSION 1.3 2015 JUNE 15 QTLeap Machine translation is a computational procedure that seeks to provide the translation of utterances
Off-line (and On-line) Text Analysis for Computational Lexicography
Offline (and Online) Text Analysis for Computational Lexicography Von der PhilosophischHistorischen Fakultät der Universität Stuttgart zur Erlangung der Würde eines Doktors der Philosophie (Dr. phil.)
SYSTRAN 混 合 策 略 汉 英 和 英 汉 机 器 翻 译 系 统
SYSTRAN Chinese-English and English-Chinese Hybrid Machine Translation Systems Jin Yang, Satoshi Enoue Jean Senellart, Tristan Croiset SYSTRAN Software, Inc. SYSTRAN SA 9333 Genesee Ave. Suite PL1 La Grande
Question template for interviews
Question template for interviews This interview template creates a framework for the interviews. The template should not be considered too restrictive. If an interview reveals information not covered by
Learning Translations of Named-Entity Phrases from Parallel Corpora
Learning Translations of Named-Entity Phrases from Parallel Corpora Robert C. Moore Microsoft Research Redmond, WA 98052, USA bobmoore@microsoft.com Abstract We develop a new approach to learning phrase
Automated Online English -Arabic Translator
Faculty of Engineering & Architecture Electrical & Computer Engineering Department Final Year Project - Spring 2006 Automated Online English -Arabic Translator Supervisor: Prof. Ali El Hajj Report Grader:
ON GETTING THE MOST OUT OF INTERNET RESOURCES TO RAISE TRANSLATION QUALITY OF PROFESSIONAL DOCUMENTATION
General and Professional Education 3/2013 pp. 21-27 ISSN 2084-1469 ON GETTING THE MOST OUT OF INTERNET RESOURCES TO RAISE TRANSLATION QUALITY OF PROFESSIONAL DOCUMENTATION Svetlana Sheremetyeva Department
Selected Topics in Applied Machine Learning: An integrating view on data analysis and learning algorithms
Selected Topics in Applied Machine Learning: An integrating view on data analysis and learning algorithms ESSLLI 2015 Barcelona, Spain http://ufal.mff.cuni.cz/esslli2015 Barbora Hladká hladka@ufal.mff.cuni.cz
CINTIL-PropBank. CINTIL-PropBank Sub-corpus id Sentences Tokens Domain Sentences for regression atsts 779 5,654 Test
CINTIL-PropBank I. Basic Information 1.1. Corpus information The CINTIL-PropBank (Branco et al., 2012) is a set of sentences annotated with their constituency structure and semantic role tags, composed
INF5820 Natural Language Processing - NLP. H2009 Jan Tore Lønning jtl@ifi.uio.no
INF5820 Natural Language Processing - NLP H2009 Jan Tore Lønning jtl@ifi.uio.no Semantic Role Labeling INF5830 Lecture 13 Nov 4, 2009 Today Some words about semantics Thematic/semantic roles PropBank &
Survey Results: Requirements and Use Cases for Linguistic Linked Data
Survey Results: Requirements and Use Cases for Linguistic Linked Data 1 Introduction This survey was conducted by the FP7 Project LIDER (http://www.lider-project.eu/) as input into the W3C Community Group
BILINGUAL TRANSLATION SYSTEM
BILINGUAL TRANSLATION SYSTEM (FOR ENGLISH AND TAMIL) Dr. S. Saraswathi Associate Professor M. Anusiya P. Kanivadhana S. Sathiya Abstract--- The project aims in developing Bilingual Translation System for
LetsMT!: A Cloud-Based Platform for Do-It-Yourself Machine Translation
LetsMT!: A Cloud-Based Platform for Do-It-Yourself Machine Translation Andrejs Vasiļjevs Raivis Skadiņš Jörg Tiedemann TILDE TILDE Uppsala University Vienbas gatve 75a, Riga Vienbas gatve 75a, Riga Box
Improving Machine Translation using Hybrid Dictionary-Graph Based Word Sense Disambiguation with Semantic and Statistical Methods
Improving Machine Translation using Hybrid Dictionary-Graph Based Word Sense Disambiguation with Semantic and Statistical Methods Ola Mohammad Ali, Mahmoud GadAlla, and Mohammad Said Abdelwahab Abstract
An Approach to Handle Idioms and Phrasal Verbs in English-Tamil Machine Translation System
An Approach to Handle Idioms and Phrasal Verbs in English-Tamil Machine Translation System Thiruumeni P G, Anand Kumar M Computational Engineering & Networking, Amrita Vishwa Vidyapeetham, Coimbatore,
ADVANTAGES AND DISADVANTAGES OF TRANSLATION MEMORY: A COST/BENEFIT ANALYSIS by Lynn E. Webb BA, San Francisco State University, 1992 Submitted in
: A COST/BENEFIT ANALYSIS by Lynn E. Webb BA, San Francisco State University, 1992 Submitted in partial satisfaction of the requirements for the Degree of MASTER OF ARTS in Translation of German Graduate
Recent developments in machine translation policy at the European Patent Office
Recent developments in machine translation policy at the European Patent Office Dr Georg Artelsmair Director European Co-operation European Patent Office Brussels, 17 November 2010 The European Patent
Automated Multilingual Text Analysis in the Europe Media Monitor (EMM) Ralf Steinberger. European Commission Joint Research Centre (JRC)
Automated Multilingual Text Analysis in the Europe Media Monitor (EMM) Ralf Steinberger European Commission Joint Research Centre (JRC) https://ec.europa.eu/jrc/en/research-topic/internet-surveillance-systems
Language Processing and the Clean Up System
ATLAS - Human Language Technologies integrated within a Multilingual Web Content Management System Svetla Koeva Department of Computational Linguistics, Institute for Bulgarian Bulgarian Academy of Sciences
Collaborative Machine Translation Service for Scientific texts
Collaborative Machine Translation Service for Scientific texts Patrik Lambert patrik.lambert@lium.univ-lemans.fr Jean Senellart Systran SA senellart@systran.fr Laurent Romary Humboldt Universität Berlin
DAM-LR at the INL Archive Formation and Local INL. Remco van Veenendaal veenendaal@inl.nl http://imdi.inl.nl 01/03/2007 DAM-LR
DAM-LR at the INL Archive Formation and Local INL Remco van Veenendaal veenendaal@inl.nl http://imdi.inl.nl Introducing Remco van Veenendaal Project manager DAM-LR Acting project manager Dutch HLT Agency
Machine Translation and the Translator
Machine Translation and the Translator Philipp Koehn 8 April 2015 About me 1 Professor at Johns Hopkins University (US), University of Edinburgh (Scotland) Author of textbook on statistical machine translation
Maskinöversättning 2008. F2 Översättningssvårigheter + Översättningsstrategier
Maskinöversättning 2008 F2 Översättningssvårigheter + Översättningsstrategier Flertydighet i källspråket poäng point, points, credit, credits, var verb ->was, were pron -> each adv -> where adj -> every
TRANSREAD LIVRABLE 3.1 QUALITY CONTROL IN HUMAN TRANSLATIONS: USE CASES AND SPECIFICATIONS. Projet ANR 201 2 CORD 01 5
Projet ANR 201 2 CORD 01 5 TRANSREAD Lecture et interaction bilingues enrichies par les données d'alignement LIVRABLE 3.1 QUALITY CONTROL IN HUMAN TRANSLATIONS: USE CASES AND SPECIFICATIONS Avril 201 4
Annotation Guidelines for Dutch-English Word Alignment
Annotation Guidelines for Dutch-English Word Alignment version 1.0 LT3 Technical Report LT3 10-01 Lieve Macken LT3 Language and Translation Technology Team Faculty of Translation Studies University College
Testing Data-Driven Learning Algorithms for PoS Tagging of Icelandic
Testing Data-Driven Learning Algorithms for PoS Tagging of Icelandic by Sigrún Helgadóttir Abstract This paper gives the results of an experiment concerned with training three different taggers on tagged
Living, Working, Breathing the toolset How Alpha CRC has incorporated memoq in its production process
Living, Working, Breathing the toolset How Alpha CRC has incorporated memoq in its production process GT 12/02/2014 Topics covered What are the global L10n challenges to solve? What are the clientside
PoS-tagging Italian texts with CORISTagger
PoS-tagging Italian texts with CORISTagger Fabio Tamburini DSLO, University of Bologna, Italy fabio.tamburini@unibo.it Abstract. This paper presents an evolution of CORISTagger [1], an high-performance
Intel s Localization BUS Initiative To XLIFF or not to XLIFF. Loïc Dufresne de Virel Localization Strategist
Intel s Localization BUS Initiative To XLIFF or not to XLIFF Loïc Dufresne de Virel Localization Strategist Intel Information Technology DISCLAIMERS I m presenting here what we are doing Still a work in
4.1 Multilingual versus bilingual systems
This chapter is devoted to some fundamental questions on the basic strategies of MT systems. These concern decisions which designers of MT systems have to address before any construction can start, and
TRANSLATING POLISH TEXTS INTO SIGN LANGUAGE IN THE TGT SYSTEM
20th IASTED International Multi-Conference Applied Informatics AI 2002, Innsbruck, Austria 2002, pp. 282-287 TRANSLATING POLISH TEXTS INTO SIGN LANGUAGE IN THE TGT SYSTEM NINA SUSZCZAŃSKA, PRZEMYSŁAW SZMAL,
MULINEX. Multilingual Indexing, Navigation and Editing Extensions for the World-Wide Web
MULINEX Multilingual Indexing, Navigation and Editing Extensions for the World-Wide Web Gregor Erbach, Günter Neumann, Hans Uszkoreit DFKI GmbH Language Technology Lab 66123 Saarbrücken Germany lt-mulinex@dfki.uni-sb.de
Automatic Mining of Internet Translation Reference Knowledge Based on Multiple Search Engines
, 22-24 October, 2014, San Francisco, USA Automatic Mining of Internet Translation Reference Knowledge Based on Multiple Search Engines Baosheng Yin, Wei Wang, Ruixue Lu, Yang Yang Abstract With the increasing
SYSTRAN v6 Quick Start Guide
SYSTRAN v6 Quick Start Guide 2 SYSTRAN v6 Quick Start Guide SYSTRAN Business Translator SYSTRAN Premium Translator Congratulations on your SYSTRAN v6 purchase which uses the latest generation of language
Research meets practice: t-survey 2005
Page 1 of 27 Research meets practice: t-survey 25 An online survey on terminology extraction and terminology management Daniel Zielinski (d.zielinski@mx.uni-saarland.de) Yamile Ramírez Safar (ramirez.yamile@googlemail.com)
Frequency Dictionary of Verb Phrase Constructions
Frequency Dictionary of Verb Phrase Constructions An automatic lexical acquisition method and its applications theses of the Ph.D. dissertation Bálint Sass supervisor: Gábor Prószéky, D.Sc. Pázmány Péter
IRIS - English-Irish Translation System
IRIS - English-Irish Translation System Mihael Arcan, Unit for Natural Language Processing of the Insight Centre for Data Analytics at the National University of Ireland, Galway Introduction about me,
A Joint Sequence Translation Model with Integrated Reordering
A Joint Sequence Translation Model with Integrated Reordering Nadir Durrani, Helmut Schmid and Alexander Fraser Institute for Natural Language Processing University of Stuttgart Introduction Generation
An Online Service for SUbtitling by MAchine Translation
SUMAT CIP-ICT-PSP-270919 An Online Service for SUbtitling by MAchine Translation Annual Public Report 2011 Editor(s): Contributor(s): Reviewer(s): Status-Version: Volha Petukhova, Arantza del Pozo Mirjam
Cross-lingual Synonymy Overlap
Cross-lingual Synonymy Overlap Anca Dinu 1, Liviu P. Dinu 2, Ana Sabina Uban 2 1 Faculty of Foreign Languages and Literatures, University of Bucharest 2 Faculty of Mathematics and Computer Science, University
TRANSLATION OF TELUGU-MARATHI AND VICE- VERSA USING RULE BASED MACHINE TRANSLATION
TRANSLATION OF TELUGU-MARATHI AND VICE- VERSA USING RULE BASED MACHINE TRANSLATION Dr. Siddhartha Ghosh 1, Sujata Thamke 2 and Kalyani U.R.S 3 1 Head of the Department of Computer Science & Engineering,