TAILIEUCHUNG - Báo cáo khoa học: "Correcting Automatic Translations through Collaborations between MT and Monolingual Target-Language Users"

Machine translation (MT) systems have improved significantly; however, their outputs often contain too many errors to communicate the intended meaning to their users. This paper describes a collaborative approach for mediating between an MT system and users who do not understand the source language and thus cannot easily detect translation mistakes on their own. Through a visualization of multiple linguistic resources, this approach enables the users to correct difficult translation errors and understand translated passages that were otherwise baffling. . | Correcting Automatic Translations through Collaborations between MT and Monolingual Target-Language Users Joshua S. Albrecht and Rebecca Hwa and G. Elisabeta Marai Department of Computer Science University of Pittsburgh jsa8 hwa marai @ Abstract Machine translation MT systems have improved significantly however their outputs often contain too many errors to communicate the intended meaning to their users. This paper describes a collaborative approach for mediating between an MT system and users who do not understand the source language and thus cannot easily detect translation mistakes on their own. Through a visualization of multiple linguistic resources this approach enables the users to correct difficult translation errors and understand translated passages that were otherwise baffling. 1 Introduction Recent advances in machine translation MT have given us some very good translation systems. They can automatically translate between many languages for a variety of texts and they are widely accessible to the public via the web. The quality of the MT outputs however is not reliably high. People who do not understand the source language may be especially baffled by the MT outputs because they have little means to recover from translation mistakes. The goal of this work is to help monolingual target-language users to obtain better translations by enabling them to identify and overcome errors produced by the MT system. We argue for a human-computer collaborative approach because both the users and the MT system have gaps in their abilities that the other could compensate. To facilitate this collaboration we propose an interface that mediates between the user and the MT system. It manages additional NLP tools for the source language and translation resources so that the user can explore this extra information to gain enough understanding of the source text to correct MT errors. The interactions between the users and the MT system may in turn offer .

• Báo cáo khoa học
• Correcting Automatic Translations
• Collaborations between MT
• Monolingual Target Language Users
• 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