tailieunhanh - Báo cáo khoa học: "A Writing Assistant for CAT and CALL"

We introduce a method for learning to predict the following grammar and text of the ongoing translation given a source text. In our approach, predictions are offered aimed at reducing users’ burden on lexical and grammar choices, and improving productivity. The method involves learning syntactic phraseology and translation equivalents. At run-time, the source and its translation prefix are sliced into ngrams to generate subsequent grammar and translation predictions. We present a prototype writing assistant, TransAhead1, that applies the method to where computer-assisted translation and language learning meet. The preliminary results show that the method has great potentials in CAT. | TransAhead A Writing Assistant for CAT and CALL Chung-chi Huang Ping-che Yang Mei-hua Chen Hung-ting Hsieh Ting-hui Kao Jason S. Chang ISA NTHU HsinChu Taiwan . III Taipei Taiwan . CS NTHU HsinChu Taiwan . u901571 maciaclark vincent732 maxis1718 schang Abstract We introduce a method for learning to predict the following grammar and text of the ongoing translation given a source text. In our approach predictions are offered aimed at reducing users burden on lexical and grammar choices and improving productivity. The method involves learning syntactic phraseology and translation equivalents. At run-time the source and its translation prefix are sliced into ngrams to generate subsequent grammar and translation predictions. We present a prototype writing assistant TransAhead1 that applies the method to where computer-assisted translation and language learning meet. The preliminary results show that the method has great potentials in CAT and CALL significant boost in translation quality is observed . 1. Introduction More and more language learners use the MT systems on the Web for language understanding or learning. However web translation systems typically suggest a usually far from perfect onebest translation and hardly interact with the user. Language learning sentence translation could be achieved more interactively and appropriately if a system recognized translation as a collaborative sequence of the user s learning and choosing from the machine-generated predictions of the next-in-line grammar and text and the machine s adapting to the user s accepting overriding the suggestions. Consider the source sentence SfflAS Mffl M fô SMÃẼ We play an important role in closing this deal . The best learning environment is probably not the one solely Available at http theSite TransAhead which for the time being only supports Chrome browsers. providing the automated translation. A good learning environment might .

• Báo cáo khoa học
• A Writing Assistant
• CAT and CALL
• Chung chi Huang
• scientific reports
• model language
• process natural language
• A First Language Oriented
• Writing Assistant System
• Mei Hua Chen
• báo cáo khoa học
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• SWAN – Scientific Writing Assistant
• Tool for Helping Scholars to Write
• Reader Friendly Manuscripts
• 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