'Mt system' diaporamas de présentation

Language Modeling

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Language Modeling for ASR

Language Modeling for ASR. Andreas Stolcke Microsoft and ICSI (based on slides from Dan Jurafsky at Stanford). Outline. What is language modeling Noisy channel and its applications The 99%: N-gram modeling and smoothing The 1%: Cache LMs Parsing-based LMs Discriminative LMs

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Why are you not (yet) using MT?

Quality Estimation for Machine Translation: different users , different needs Lucia Specia L.Specia@wlv.ac.uk http://pers-www.wlv.ac.uk/~in1316/ JEC Workshop October 14 th 2011.

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Arabic NLP: Overview, the State of the Art Challenges and Opportunities

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Viswanatha Naidu Y IIIT-Hyderabad 20-02-09 vnaidu@research.iiit.ac.in

SCONLI-3. Corpus Based study of Relative clauses in Hindi & Telugu Transfer grammar rules for relative clauses. Viswanatha Naidu Y IIIT-Hyderabad 20-02-09 vnaidu@research.iiit.ac.in. OUTLINE. Introduction Hindi Relative clause overview Telugu Relative clause overview

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An Introduction to MT Evaluation

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Natural Language Processing

Natural Language Processing. Introduction. Any Light at The End of The Tunnel ?. Yahoo, Google, Microsoft ? Information Retrieval Monster.com, HotJobs.com (Job finders) ? Information Extraction + Information Retrieval Systran powers Babelfish ? Machine Translation

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Evaluating the Waspbench

Evaluating the Waspbench. A Lexicography Tool Incorporating Word Sense Disambiguation Rob Koeling, Adam Kilgarriff, David Tugwell, Roger Evans ITRI, University of Brighton Credits: UK EPSRC grant WASPS, M34971. Lexicographers need NLP. NLP needs lexicography. Word senses: nowhere truer.

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A Discriminative Syntactic Word Order Model for MT

A Discriminative Syntactic Word Order Model for MT. Pi-Chuan Chang 1 , Kristina Toutanova 2 1 Stanford University 2 Microsoft Research. Assuming the existence of a Word Choice Model. We focus on a Word Order Model which predicts the order of the words. Introduction (1/2).

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Optimizing Chinese Word Segmentation for MT performance

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The Effect of Translation Quality in MT-Based Cross-Language Information Retrieval

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Stephen Doherty, CNGL/SALIS s tephen.doherty2@mail.dcu.ie

Current Research A comparative investigation of the readability and comprehensibility of SMT and RBMT output for controlled and uncontrolled input. Stephen Doherty, CNGL/SALIS s tephen.doherty2@mail.dcu.ie. Overview. Past Research Readability & Comprehensibility Controlled Language

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New Directions in Machine Translation Introduction

New Directions in Machine Translation Introduction. ??? ????? ??? / ???. Why MT Matters?. Economics Costs ? / Quality ? / Turnaround ? Many MT developers, customers, and sponsors have already invested a lot for years. Politics Multi-lingual Countries / Minority Languages

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Wrapper Syntax for Example-Based Machine Translation

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Josef van Genabith & Andy Way TransBooster (2003-2006)

Previous MT Work & GramLab. Josef van Genabith & Andy Way TransBooster (2003-2006) LaDEva: Labelled Dependency-Based MT Evaluation (2006-2008) GramLab (2001-2008). TransBooster. TransBooster (2003-2006) Enterprise Ireland funded Basic Research Project

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Embedded MT Systems

Embedded MT Systems. Definition: A computational system with one or more MT engines embedded among its components. These systems accept various well-formed and degraded types of multilingual and multi-modal input, including * hard-copy pages (original and OCR-ed images)

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On the Value of Machine Translation Adaptation

LREC Workshop: Automatic and Manual Metrics for Operational Translation Evaluation (MTE 2014) May 26, 2014. Approved for Public Release; Distribution Unlimited. 14-1556. On the Value of Machine Translation Adaptation. Stacey Bailey and Keith Miller. MT, DT, DTMT.

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