TAILIEUCHUNG - Báo cáo khoa học: "Determining the placement of German verbs in English–to–German SMT"

When translating English to German, existing reordering models often cannot model the long-range reorderings needed to generate German translations with verbs in the correct position. We reorder English as a preprocessing step for English-to-German SMT. We use a sequence of hand-crafted reordering rules applied to English parse trees. The reordering rules place English verbal elements in the positions within the clause they will have in the German translation. This is a difficult problem, as German verbal elements can appear in different positions within a clause (in contrast with English verbal elements, whose positions do not vary as much). We. | Determining the placement of German verbs in English-to-German SMT Anita Gojun Alexander Fraser Institute for Natural Language Processing University of Stuttgart Germany gojunaa fraser @ Abstract When translating English to German existing reordering models often cannot model the long-range reorderings needed to generate German translations with verbs in the correct position. We reorder English as a preprocessing step for English-to-German SMT. We use a sequence of hand-crafted reordering rules applied to English parse trees. The reordering rules place English verbal elements in the positions within the clause they will have in the German translation. This is a difficult problem as German verbal elements can appear in different positions within a clause in contrast with English verbal elements whose positions do not vary as much . We obtain a significant improvement in translation performance. 1 Introduction Phrase-based SMT PSMT systems translate word sequences phrases from a source language into a target language performing reordering of target phrases in order to generate a fluent target language output. The reordering models such as for example the models implemented in Moses Koehn et al. 2007 are often limited to a certain reordering range since reordering beyond this distance cannot be performed accurately. This results in problems of fluency for language pairs with large differences in constituent order such as English and German. When translating from English to German verbs in the German output are often incorrectly left near their position in English creating problems of fluency. Verbs are also often omitted since the distortion model cannot move verbs to positions which are licensed by the German language model making the translations difficult to understand. A common approach for handling the long-range reordering problem within PSMT is performing syntax-based or part-of-speech-based POS-based reordering of the input as a .

• Báo cáo khoa học
• Determining the placement of German verbs
• English–to–German SMT
• Anita Gojun Alexander
• 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
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• 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
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• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
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• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
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• Douglas E
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• Kathleen R
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• MENTING A DATABASE
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• Jeffrey Conklin David D
• McDonald
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• Stuart C
• Shapiro
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• Mark H
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