Extracting translation relations for humanreadable dictionaries from bilingual text
|
|
|
- Roland Ferguson
- 10 years ago
- Views:
Transcription
1 Extracting translation relations for humanreadable dictionaries from bilingual text
2 Overview 1. Company 2. Translate pro 12.1 and AutoLearn<word> 3. Translation workflow 4. Extraction method 5. Extended AutoLearn with selection restrictions 6. Improving accuracy, coverage and availability 7. On-the-fly extraction TeKom Lingenio
3 Company Funded in 1999 Spin-off of the IBM research center Germany located in Heidelberg develops and markets language technology software and services. Core compentence machine translation electronic dictionaries text analysis (morphology, syntax, semantics) Several research projects TeKom Lingenio
4 Translate pro 12.1 Single user versions for professional translators and private use including dictionaries with context-sensitive search functions TeKom Lingenio
5 Translate pro 12.1 Corporate solutions Client/Server networks for workgroups Lingenio Translation Server: web-based solutions for company-wide intranets TeKom Lingenio
6 Translate pro 12.1 Integration via Plug-Ins into Publishing Tools Wordpress, CAT-Tools Trados OmegaT, TeKom Lingenio
7 Translate pro 12.1 Translation Center MS Office Plug-Ins Browser Plug-Ins (IE, Firefox) Pdf translation TeKom Lingenio
8 Translation Center User dictionaries edition, settings Translation Memories selection, settings Automatic extraction of dictionary entries Postediting: Alternative translations Assistant: Unknown words, Statistics, settings, TeKom Lingenio
9 AutoLearn<word> extracts suggestions for dictionary entries from postedited MT Translation memories TeKom Lingenio
10 AutoLearn<word> creates suggestions from postedited text TeKom Lingenio
11 AutoLearn<word> creates suggestions from postedited text TeKom Lingenio
12 AutoLearn<word> creates suggestions from translation memory sentence pairs TeKom Lingenio
13 AutoLearn<word> suggestions extracted from translation memory sentence pairs TeKom Lingenio
14 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 TeKom Lingenio
15 AutoLearn<word> suggestions can be added to dictionary single relations or all TeKom Lingenio
16 Dictionary entries assigned to suggestions make use of morpho-syntactic & semantic information & defaults of the MT system can be edited TeKom Lingenio
17 AutoLearn entries adapt the translation to the references extracted TeKom Lingenio
18 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 workflow TeKom Lingenio
19 AutoLearn<word> bilingual texts European insurance regulation TeKom Lingenio
20 AutoLearn<word> align & import into translation memory TeKom Lingenio
21 AutoLearn<word> extract translation suggestions from single sentence pairs TeKom Lingenio
22 AutoLearn<word> extract translation suggestions from single sentence pairs TeKom Lingenio
23 AutoLearn<word> or from complete translation memories TeKom Lingenio
24 AutoLearn<word> from complete translation memories TeKom Lingenio
25 AutoLearn<word> - Extraction method 1. Translation relations from system dictionaries 2. Structures assigned to source and target sentence by the analysis components of the MT system TeKom Lingenio
26 Example Die Lithofazien-Analyse des oberen Teils der Pliozän-Schicht im Valdelsa-Becken (Mittelitalien) hat eine gewisse Anzahl von Umweltablagerungen ergeben, von der Schwemm- zur Küsten- und zur Meeresebene. Lithofacies analysis of the upper part of the Pliocene succession of the Valdelsa basin (central Italy) unravelled a number of depositional environments, ranging from alluvial plain to coastal, to marine TeKom Lingenio
27 Example Die Lithofazien-Analyse der Pliozän-Schicht hat eine gewisse Anzahl von Umweltablagerungen ergeben. Lithofacies analysis of the Pliocene succession unravelled a number of depositional environments TeKom Lingenio
28 Dependence grammar structures TeKom Lingenio
29 Dependence grammar structures + transfer knowledge TeKom Lingenio
30 Dependence grammar structures + transfer knowledge (+ statistics) TeKom Lingenio
31 Dependence grammar structures + transfer knowledge (+ statistics) Derive new relations TeKom Lingenio
32 Dependence grammar structures + transfer knowledge (+ statistics) Derive new relations AutoLearn<word> TeKom Lingenio
33 Do more! Use analysis constraints! syntactic constraints semantic constraints morphological constraints 33
34 Extended AutoLearn with selection restrictions TeKom Lingenio
35 Extended AutoLearn with selection restrictions genitive object constraint direct object constraints 35
36 Extended AutoLearn with selection restrictions extract restrictions Lithofazien-Analyse ergibt Anzahl Umweltablagerungen ~ unravel weaken conditions Analyse ergibt Ablagerung Vorgang ergibt Ergebnis Select conditions by evaluating occurrences in corpora Analyse/Vorgang ergibt Rückstand/ Ergebnis ~ unravel, yield? 36
37 Extended AutoLearn soon: version 12.5 with selection restrictions 37
38 Extended AutoLearn soon: version 12.5 with selection restrictions supporting research: improve accuracy and coverage 38
39 Improving accuracy and coverage EU Marie Curie project (Hybrid high quality machine translation) BMWi project FlexNeuroTrans (Flexible MT for medium-sized businesses using neural nets) combination of rule-based and statistical methods extract information from the internet, TeKom Lingenio
40 AutoLearn<word> information Example: European insurance regulation search bilingual text (on the fly) that suits information requirement For example via Wikipedia, TeKom Lingenio
41 AutoLearn<word> information store & examine extracted texts TeKom Lingenio
42 Availability for translation service (Lingenio Translation Server LTS) for CAT-tools publishing tools (Wordpress,..) Intranet solutions AutoLearn<word> TeKom Lingenio
43 Improving availability for multilingual platforms TeKom Lingenio
44 On-the-fly extraction Text to be processed TeKom Lingenio
45 Summary: products & research 1. version 12.1 AutoLearn<word> (for several parts of speech & multiwords) 2. version 12.5 (soon: with selection restrictions) 3. learning, user dictionaries & memories available for Lingenio Translation Server (for CAT-tools, publishing and intranet) 4. supporting research for improving accuracy, coverage and onthe-fly extraction of translation information TeKom Lingenio
46 Thank you for your attention! Questions? (please visit us at stand 420)
Hybrid Strategies. for better products and shorter time-to-market
Hybrid Strategies for better products and shorter time-to-market Background Manufacturer of language technology software & services Spin-off of the research center of Germany/Heidelberg Founded in 1999,
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
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
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
Computer Aided Translation
Computer Aided Translation Philipp Koehn 30 April 2015 Why Machine Translation? 1 Assimilation reader initiates translation, wants to know content user is tolerant of inferior quality focus of majority
Machine Translation Computer Aided Translation Machine Language Processing
Machine Translation Computer Aided Translation Machine Language Processing Martin Kappus ([email protected]) 1 Machine Translation Computer-Aided Translation Agenda Machine Translation Introduction History
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!
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,
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
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
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
SYSTRAN Enterprise Server 7 Online Tools User Guide. Chapter 1: Overview... 1 SYSTRAN Enterprise Server 7 Overview... 2
g SYSTRAN Enterprise Server 7 Online Tools User Guide i Table of Contents Chapter 1: Overview... 1 SYSTRAN Enterprise Server 7 Overview... 2 SYSTRAN Enterprise Server 7 Components... 2 SYSTRAN Translation
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
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
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
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
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
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
Structure of the presentation
Terminology and Technical Documentation Translation technology and workflowmanagement Structure of the presentation Source text control Issues in translation and multilingual document management : Case
The Language Grid The Language Grid combines users language resources and machine translators to produce high-quality translation that is customized
The Language Grid The Language Grid combines users language resources and machine translators to produce high-quality translation that is customized to each field. The Language Grid, a software that provides
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
Your single-source partner for corporate product communication. Transit NXT Evolution. from Service Pack 0 to Service Pack 8
Transit NXT Evolution from Service Pack 0 to Service Pack 8 April 2009: Transit NXT Service Pack 0 (Version 4.0.0.671) Additional versions of DTP programs supported: InDesign CS3 and FrameMaker 9 Additional
Translation and Localization Services
Translation and Localization Services Company Overview InterSol, Inc., a California corporation founded in 1996, provides clients with international language solutions. InterSol delivers multilingual solutions
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
Machine Translation as a translator's tool. Oleg Vigodsky Argonaut Ltd. (Translation Agency)
Machine Translation as a translator's tool Oleg Vigodsky Argonaut Ltd. (Translation Agency) About Argonaut Ltd. Documentation translation (Telecom + IT) from English into Russian, since 1992 Main customers:
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
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:
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
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
Multilingual Term Extraction as a Service from Acrolinx. Ben Gottesman Michael Klemme Acrolinx CHAT2013
Multilingual Term Extraction as a Service from Acrolinx Ben Gottesman Michael Klemme Acrolinx CHAT2013 Definitions term extraction: automatically identifying potential terms in a document (corpus) multilingual
SYSTRAN 6 Desktop User Guide. Chapter 1: Overview... 1 SYSTRAN Desktop Products Overview... 2
SYSTRAN 6 Desktop User Guide i Table of Contents Chapter 1: Overview... 1 SYSTRAN Desktop Products Overview... 2 SYSTRAN 6 Product Comparison... 2 Special Terms Used in this Guide... 4 About Language Translation
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,
The history of machine translation in a nutshell
The history of machine translation in a nutshell John Hutchins [Web: http://ourworld.compuserve.com/homepages/wjhutchins] [Latest revision: November 2005] 1. Before the computer 2. The pioneers, 1947-1954
Fully Automatic High Quality Machine Translation of. Restricted Text: A Case Study
[Translating and the Computer 28, November 2006 (London: Aslib, 2006)] Fully Automatic High Quality Machine Translation of Restricted Text: A Case Study Uwe Muegge ([email protected], [email protected])
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
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
Localization Profile 2014
Localization Profile 2014 January 2014 Localization Profile 1 www.esrinea.com Copyright Notice 2014 Esri Northeast Africa. All rights reserved. No part of this document may be reproduced or transmitted
Multilingual and mixed-lingual TTS applications
Multilingual and mixed-lingual TTS applications LangTech 2003 November 24, 2003 Simona Fina, Manager Linguistics Real-life texts need mixed-lingual analysis Agenda Short presentation of SVOX Challenges
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
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.
Transit NXT Product Guide Service Pack 7 09/2013
Transit NXT Product Guide Service Pack 7 09/2013 Initial overview In this document, you will find out which product variant and which installation type suits your requirements. You are at the right place
Integra(on of human and machine transla(on. Marcello Federico Fondazione Bruno Kessler MT Marathon, Prague, Sept 2013
Integra(on of human and machine transla(on Marcello Federico Fondazione Bruno Kessler MT Marathon, Prague, Sept 2013 Motivation Human translation (HT) worldwide demand for translation services has accelerated,
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,
A web-based multilingual help desk
LTC-Communicator: A web-based multilingual help desk Nigel Goffe The Language Technology Centre Ltd Kingston upon Thames Abstract Software vendors operating in international markets face two problems:
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,
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)
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
Statistical Machine Translation
Statistical Machine Translation What works and what does not Andreas Maletti Universität Stuttgart [email protected] Stuttgart May 14, 2013 Statistical Machine Translation A. Maletti 1 Main
KantanMT.com. www.kantanmt.com. The world s #1 MT Platform. No Hardware. No Software. No Hassle MT.
KantanMT.com No Hardware. No Software. No Hassle MT. The world s #1 MT Platform Communicate globally, easily! Create customized language solutions in the cloud. www.kantanmt.com What is KantanMT.com? KantanMT
Neural Machine Transla/on for Spoken Language Domains. Thang Luong IWSLT 2015 (Joint work with Chris Manning)
Neural Machine Transla/on for Spoken Language Domains Thang Luong IWSLT 2015 (Joint work with Chris Manning) Neural Machine Transla/on (NMT) End- to- end neural approach to MT: Simple and coherent. Achieved
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
Translation Management System
Translation Management System LINGOTEK PRODUCT BRIEF Table of Contents Current Lingotek Customers...2 The Challenge of Translation and Localization Today...3 Lingotek s Complete Offering...4 The Lingotek
Natural Language Database Interface for the Community Based Monitoring System *
Natural Language Database Interface for the Community Based Monitoring System * Krissanne Kaye Garcia, Ma. Angelica Lumain, Jose Antonio Wong, Jhovee Gerard Yap, Charibeth Cheng De La Salle University
Machine vs. Human Translation Scott Bass, Advanced Language Translation Inc.
Machine vs. Human Translation Scott Bass, Advanced Language Translation Inc. Using computers to translate text from one language to another (referred to as machine translation [MT]) no longer faces the
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, [email protected] Tools in the Terminology Life Cycle Extraction
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
XTM for Language Service Providers Explained
XTM for Language Service Providers Explained 1. Introduction There is a new generation of Computer Assisted Translation (CAT) tools available based on the latest Web 2.0 technology. These systems are more
Cross-Language Information Retrieval by Domain Restriction using Web Directory Structure
Cross-Language Information Retrieval by Domain Restriction using Web Directory Structure Fuminori Kimura Faculty of Culture and Information Science, Doshisha University 1 3 Miyakodani Tatara, Kyoutanabe-shi,
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
Online free translation services
[Translating and the Computer 24: proceedings of the International Conference 21-22 November 2002, London (Aslib, 2002)] Online free translation services Thei Zervaki [email protected] Introduction
Web-based automatic translation: the Yandex.Translate API
Maarten van Hees [email protected] Web-based automatic translation: the Yandex.Translate API Paulina Kozłowska [email protected] Nana Tian [email protected] ABSTRACT Yandex.Translate
GATE Mímir and cloud services. Multi-paradigm indexing and search tool Pay-as-you-go large-scale annotation
GATE Mímir and cloud services Multi-paradigm indexing and search tool Pay-as-you-go large-scale annotation GATE Mímir GATE Mímir is an indexing system for GATE documents. Mímir can index: Text: the original
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
Software Cost. Discounted STS Rate Units Total $0.00 $0.00 $0.00 $0.00 Total $0.00
Cost Form This cost form has been provided to assist respondents in submitting costs associated by deliverable. Remember that all costs are to be the firm, fixed price of the deliverable and project total.
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
Convergence of Translation Memory and Statistical Machine Translation
Convergence of Translation Memory and Statistical Machine Translation Philipp Koehn and Jean Senellart 4 November 2010 Progress in Translation Automation 1 Translation Memory (TM) translators store past
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
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
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
Using the BNC to create and develop educational materials and a website for learners of English
Using the BNC to create and develop educational materials and a website for learners of English Danny Minn a, Hiroshi Sano b, Marie Ino b and Takahiro Nakamura c a Kitakyushu University b Tokyo University
How To Translate English To Yoruba Language To Yoranuva
International Journal of Language and Linguistics 2015; 3(3): 154-159 Published online May 11, 2015 (http://www.sciencepublishinggroup.com/j/ijll) doi: 10.11648/j.ijll.20150303.17 ISSN: 2330-0205 (Print);
Introduction to formal semantics -
Introduction to formal semantics - Introduction to formal semantics 1 / 25 structure Motivation - Philosophy paradox antinomy division in object und Meta language Semiotics syntax semantics Pragmatics
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,
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.
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:
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