SYSTEMS AND TOOLS FOR MACHINE TRANSLATION

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1 Universitat Politècnica de València Master en Inteligencia Artificial, Renoconocimiento de Formas e Imagen Digital Curs SYSTEMS AND TOOLS FOR MACHINE TRANSLATION Francisco Casacuberta fcn@iti.upv.es Enrique Vidal evidal@iti.upv.es June 4, 2007 IARFID-UPV Introduction to IARFID-UPV June 4, 2007 SMT-1: 1

2 Introduction to IARFID-UPV June 4, 2007 SMT-1: 2 General scheme for MT Introduction to source target PRE-EDITING TRANSLATION POST-EDITING While the number of errors and bad constructions is high, post-editing can make the result useful. Many problems could have been avoided by making the source text simpler. IARFID-UPV June 4, 2007 SMT-1: 3

3 Approaches to MT: Technologies Introduction to (Linguistic) knowledge-based methods (Memorized) example-based methods Translation memories Statistical models Alignment models Finite-state models Neural networks Hybrid models IARFID-UPV June 4, 2007 SMT-1: 4 Linguistic resources and tools Introduction to Dictionaries Morpho-syntactic taggers Shallow parsers Chunkers Grammars Corpora Paragraph-aligned and labeled corpora IARFID-UPV June 4, 2007 SMT-1: 5

4 Assessment Introduction to Test sentences Subjective evaluation based on the number of words that need to be corrected or deleted Test sentences with reference translation Automatic assessment Editing Distances: Translation Word Error Rate (TWER) Multireference TWER N-gram based: BLUE and NIST score IARFID-UPV June 4, 2007 SMT-1: 6 Introduction to Computer assisted translation (CAT) Do not attempt fully automated MT Aim at high-quality results Let the human translator fully command the process Allow for tight human-machine cooperation Aim to increase human translator productivity Ergonomic issues and multimodality: keyboard, mouse, speech,... IARFID-UPV June 4, 2007 SMT-1: 7

5 Introduction to Typical computer assisted translation scenario Text prediction based on both the source-language text to be translated and preceeding text that has been validated by the user. For each source sentence or paragraph to be translated: 1. The system provides its best (or N-best) translation suggestion 2. The user selects a correct part (typically a prefix) of this suggestion and starts amending the remaining part or entering new text by him/herself 3. After each user-entered word (or key-stroke), the system recomputes its best suggestion(s), thereby starting a new human-system interaction cycle. IARFID-UPV June 4, 2007 SMT-1: 8 Introduction to IARFID-UPV June 4, 2007 SMT-1: 9

6 Web text translation systems Introduction to internostrum: SisHiTra: sishitra/ A statistical translator: IARFID-UPV June 4, 2007 SMT-1: 10 Web text translation systems Introduction to SYSTRAN: ALTAVISTA (SYSTRAN): Google: IBM WebSphere: WorldLingo: Free2ProfessionalTranslation: TranslateNow: Prompt-Online: IARFID-UPV June 4, 2007 SMT-1: 11

7 Web text translation systems Introduction to El País: El Mundo (Reverso): IARFID-UPV June 4, 2007 SMT-1: 12 Office text translation systems Introduction to SYSTRAN: SALT: WebSphere: IARFID-UPV June 4, 2007 SMT-1: 13

8 Introduction to Computer-assisted translation systems TRANSTYPE: Déjàvu: TRADOS: Sakhr Translator Workbench: IARFID-UPV June 4, 2007 SMT-1: 14 Speech translation systems Introduction to EUTRANS: Anuvaad (ATT): srini/projects/anuvaad/home.html IBM ViaVoice Translator 1.0: IARFID-UPV June 4, 2007 SMT-1: 15

9 Introduction to IARFID-UPV June 4, 2007 SMT-1: 16 Bilingual dictionaries Introduction to List of dictionaries WordReference LexiCool TravLang IARFID-UPV June 4, 2007 SMT-1: 17

10 Statistical tools Introduction to GIZA++ The ISI ReWrite Pharaoh Thot Moses IARFID-UPV June 4, 2007 SMT-1: 18 Introduction to IARFID-UPV June 4, 2007 SMT-1: 19

11 Giza++ and SRLIM Introduction to GIZA++: Training of statistical translation models redpony/software/ SRLIM: The SRI Language Modeling Toolkit IARFID-UPV June 4, 2007 SMT-1: 20 Introduction to IARFID-UPV June 4, 2007 SMT-1: 21

12 Introduction to IARFID-UPV June 4, 2007 SMT-1: 22 Introduction to IARFID-UPV June 4, 2007 SMT-1: 23

13 Introduction to IARFID-UPV June 4, 2007 SMT-1: 24

Using Perceptual Context to Ground Language

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