TAILIEUCHUNG - Báo cáo khoa học: "Comparison of Alignment Templates and Maximum Entropy Models for Natural Language Understanding"

In this paper we compare two approaches to natural language understanding (NLU). The first approach is derived from the field of statistical machine translation (MT), whereas the other uses the maximum entropy (ME) framework. Starting with an annotated corpus, we describe the problem of NLU as a translation from a source sentence to a formal language target sentence. We mainly focus on the quality of the different alignment and ME models and show that the direct ME approach outperforms the alignment templates method. . | Comparison of Alignment Templates and Maximum Entropy Models for Natural Language Understanding Oliver Bender Klaus Macherey Franz Josef Och and Hermann Ney Lehrstuhl fur Informatik VI Computer Science Department RWTH Aachen - University of Technology D-52056 Aachen Germany bender och ney @ Abstract In this paper we compare two approaches to natural language understanding NLU . The first approach is derived from the field of statistical machine translation MT whereas the other uses the maximum entropy ME framework. Starting with an annotated corpus we describe the problem of NLU as a translation from a source sentence to a formal language target sentence. We mainly focus on the quality of the different alignment and ME models and show that the direct ME approach outperforms the alignment templates method. 1 Introduction The objective of natural language understanding NLU is to extract all the information from a natural language based input which are relevant for a specific task. Typical applications using NLU components are spoken dialogue systems Levin and Pieraccini 1995 or speech-to-speech translation systems Zhou et al. 2002 . In this paper we present two approaches for analyzing the semantics of natural language inputs and discuss their advantages and drawbacks. The first approach is derived from the field of statistical machine translation MT and is based on the source-channel paradigm Brown et al. 1993 . Here we apply a method called alignment templates Och et al. 1999 . The alternative ap- ich wilrde gerne von Koln nach Miinchen fahren @want_question origin destination @going Figure 1 Example of a word concept mapping. proach uses the maximum entropy ME framework Berger et al. 1996 . For both frameworks the objective can be described as follows. Given a natural source sentence we choose the formal target language sentence e .ej with the highest probability among all possible target sentences ềf argmax Fr e I 1 cỉ - í

• Báo cáo khoa học
• Comparison of Alignment Templates
• Maximum Entropy Models
• Natural Language Understanding
• 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
• 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