tailieunhanh - Báo cáo khoa học: "Computing Consensus Translation from Multiple Machine Translation Systems Using Enhanced Hypotheses Alignment"

This paper describes a novel method for computing a consensus translation from the outputs of multiple machine translation (MT) systems. The outputs are combined and a possibly new translation hypothesis can be generated. Similarly to the well-established ROVER approach of (Fiscus, 1997) for combining speech recognition hypotheses, the consensus translation is computed by voting on a confusion network. To create the confusion network, we produce pairwise word alignments of the original machine translation hypotheses with an enhanced statistical alignment algorithm that explicitly models word reordering. . | Computing Consensus Translation from Multiple Machine Translation Systems Using Enhanced Hypotheses Alignment Evgeny Matusov Nicola Ueffing Hermann Ney Lehrstuhl fur Informatik VI - Computer Science Department RWTH Aachen University Aachen Germany. matusov ueffing ney @ Abstract This paper describes a novel method for computing a consensus translation from the outputs of multiple machine translation MT systems. The outputs are combined and a possibly new translation hypothesis can be generated. Similarly to the well-established ROVER approach of Fiscus 1997 for combining speech recognition hypotheses the consensus translation is computed by voting on a confusion network. To create the confusion network we produce pairwise word alignments of the original machine translation hypotheses with an enhanced statistical alignment algorithm that explicitly models word reordering. The context of a whole document of translations rather than a single sentence is taken into account to produce the alignment. The proposed alignment and voting approach was evaluated on several machine translation tasks including a large vocabulary task. The method was also tested in the framework of multi-source and speech translation. On all tasks and conditions we achieved significant improvements in translation quality increasing e. g. the BLEU score by as much as 15 relative. 1 Introduction In this work we describe a novel technique for computing a consensus translation from the outputs of multiple machine translation systems. Combining outputs from different systems was shown to be quite successful in automatic speech recognition ASR . Voting schemes like the ROVER approach of Fiscus 1997 use edit distance alignment and time information to create confusion networks from the output of several ASR systems. Some research on multi-engine machine translation has also been performed in recent years. The most straightforward approaches simply select for each sentence one of

• Báo cáo khoa học
• Computing Consensus Translation
• Multiple Machine Translation Systems
• Enhanced Hypotheses Alignment
• 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
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• Taxonomy
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• Individuals in Natural
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• Natural Language Processing
• Mark H
• Bursteln