tailieunhanh - Báo cáo khoa học: "Using POS Information for Statistical Machine Translation into Morphologically Rich Languages"

When translating from languages with hardly any inflectional morphology like English into morphologically rich languages, the English word forms often do not contain enough information for producing the correct fullform in the target language. We investigate methods for improving the quality of such translations by making use of part-ofspeech information and maximum entropy modeling. Results for translations from English into Spanish and Catalan are presented on the LC-STAR corpus which consists of spontaneously spoken dialogues in the domain of appointment scheduling and travel planning. . | Using POS Information for Statistical Machine Translation into Morphologically Rich Languages Nicola Ueffing and Hermann Ney Lehrstuhl fur Informatik VI - Computer Science Department RWTH Aachen - University of Technology ueffing ney @ Abstract When translating from languages with hardly any inflectional morphology like English into morphologically rich languages the English word forms often do not contain enough information for producing the correct fullform in the target language. We investigate methods for improving the quality of such translations by making use of part-of-speech information and maximum entropy modeling. Results for translations from English into Spanish and Catalan are presented on the LC-STAR corpus which consists of spontaneously spoken dialogues in the domain of appointment scheduling and travel planning. 1 Introduction In this paper we address the question of how part-of-speech POS information can help improving the quality of Statistical Machine Translation SMT . One of the main problems when translating from a language with hardly any inflectional morphology which is English in our experiments into one with richer morphology here Spanish and Catalan is the production of the correct inflected form in the target language. We introduce transformations to the English string that are based on the part-of-speech information and show how this knowledge source can help SMT. Systematic evaluations will show that the quality of the gen erated translations is improved. The transformations we apply are the following Treatment of verbs In Catalan and Spanish the pronoun before a verb is often omitted and instead the person is expressed via the ending of the verb. The same holds for future tense and for the modes expressed through would and should in English. Since this makes it hard to generate the correct translation of a given English verb we propose a method resulting in English word forms containing sufficient information. .

• Báo cáo khoa học
• Using POS Information
• Statistical Machine Translation
• Morphologically Rich Languages
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• Long Papers
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln