tailieunhanh - Báo cáo khoa học: "MACHINE TRANSLATION : WHAT TYPE OF POST-EDITING ON WHAT TYPE OF DOCUMENTSFOR WHAT TYPE OF USERS"

Various typologies of technical and seientifical texts nave already been proposeO bv authors involved in multilingual transfer problems. They were usually aimed at a better knowledge of the criteria for deciding if a document has to be or can be machine translated. Such a typology could also lead to a better knowledge of the typical errors occuring, and so lead to more appropriate post-editing, as well as to improvements in the system. Raw translations being usable, as they are quite often for rapid information needs, it is important to draw the limits between a style adequate for rapid information,. | MACHINE TRANSLATION WHAT TYPE OF POST-EDITING ON WHAT TYPE OF DOCUMENTS FOR WHAT TYPE OF USERS Anne-Marie LAURIAN Centre National de la Recherche Scientifique Université de la Sorbonne Nouvelle - Paris III 19 rue des Bernardins 75ŨU5 Paris France ABSTRACT Various typologies of technical and scientifical texts nave already been proposed by authors involved in multilingual transfer problems. They were usually aimed at a better knowledge of the criteria for deciding if a document has to be or can be machine translated. Such a typology could also lead to a better knowledge of the typical errors oc-curing and so lead to more appropriate post-editing as well as to improvements in the system. Raw translations being usable as they are quite often for rapid information needs it is important to draw the limits between a style adequate for rapid information and an elegant high quality style such as required for information large dissemination style could be given a new definition through a linguistic analysis based on machine translation on communication situations and on the users requirements and satisfaction. I. MACHINE TRANSLATION AND POST-EDITING A EUROPEAN EXAMPLE Machine translation is often considered as a project an experimental process if not an impossible dream. Translation theoreticians would sav no machine can understand the meaning of a text and re-express it in an other language so no machine can translate. The debate is about the necessity of a deep semantic understanding for translating opposed to a language structure knowledge to be sufficient to produce a translation. The usual debate is thus about the ideal concept each one has of what a translation should be. Translation can only be defined in particular situations regarding particular documents. And machine translation is only to be used for certain types of documents to be handled a certain way. Mv observations are based on several studies I carried out on the SYSTRAN output produced in Luxembourg .

• Báo cáo khoa học
• MACHINE TRANSLATION
• TYPE OF POST EDITING ON WHAT TYPE OF DOCUMENTSFOR
• TYPE OF USERS
• scientific reports
• model language
• process natural language
• N gram based Statistical
• Machine Translation versus Syntax Augmented Machine Translation
• comparison and system combination
• Human translation
• Quality of translation
• Linguistic criteria
• Strengths and weaknesses
• Construction and architecture sector
• Mixing Multiple Translation Models
• Statistical Machine Translation
• SMT
• báo cáo khoa học
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• Translation Model Size Reduction
• Hierarchical Phrase based
• Translation Model Adaptation
• Monolingual Topic Information
• Balancing User Effort and Translation Error
• Interactive Machine Translation
• Confidence Measures
• Improving On line Handwritten Recognition
• Translation Models
• Multimodal Interactive Machine Translation
• Name Translation
• Learning When to Transliterate
• xử lý ngôn ngữ tự nhiên
• A CONSIDERATION ON THE CONCEPTS STRUCTURE
• LANGUAGE IN RELATION TO SELECTIONS OF TRANSLATION EQUIVALENTS OF VERBS
• MACHINE TRANSLATION SYSTEMS
• DEALING WITH INCOMPLETENESS
• LINGUISTIC KNOWLEDGE IN LANGUAGE TRANSLATION TRANSFER AND GENERATION STAGE
• MU MACHINE TRANSLATION PROJECT
• Perplexity Minimization
• Translation Model Domain Adaptation
• Improving Pronoun Translation
• Liane Guillou
• Automatic Construction
• Machine Translation Knowledge
• Translation Literalness
• Computing Consensus Translation
• Multiple Machine Translation Systems
• Enhanced Hypotheses Alignment
• A Discriminative Latent Variable Model
• A Discriminative Latent Variable Model for Statistical Machine Translation
• Machine Translation will not Work
• FORUM ON MACHINE TRANSLATION
• Martin Kay Xerox Palo Alto
• Machine Translation already does Work
• Margaret King
• Domain adaptation
• The English Vietnamese language pair
• Low resource domains
• A machine learning
• the automatic evaluation
• mô hình ngôn ngữ
• Sciences and humanities
• Real world oriented machine translators
• Multiple reference points
• Occupational segregation
• Khoa học máy tính
• Tạp chí khoa học
• Natural Language Processing
• Phrase based Statistical Machine Translation
• translation of russian technical literature by machine
• James W
• Perry
• Mechanical Translation
• Machine Translation Development at the University of Washington
• Erwin Reifle
• The Work on Machine Translation in the Soviet Union
• V
• Yu
• Rozentsveig
• Studies in Machine Translation—8 Manual for Postediting Russian Text
• H
• P
• Edmundson