tailieunhanh - Báo cáo khoa học: "Generating statistical language models from interpretation grammars in dialogue systems"

In this paper, we explore statistical language modelling for a speech-enabled MP3 player application by generating a corpus from the interpretation grammar written for the application with the Grammatical Framework (GF) (Ranta, 2004). We create a statistical language model (SLM) directly from our interpretation grammar and compare recognition performance of this model against a speech recognition grammar compiled from the same GF interpretation grammar. The results show a relative Word Error Rate (WER) reduction of 37% for the SLM derived from the interpretation grammar while maintaining a low in-grammar WER comparable to that associated with the speech recognition grammar | Generating statistical language models from interpretation grammars in dialogue systems Rebecca Jonson Dept. of Linguistics Goteborg University and GSLT rj@ Abstract In this paper we explore statistical language modelling for a speech-enabled MP3 player application by generating a corpus from the interpretation grammar written for the application with the Grammatical Framework GF Ranta 2004 . We create a statistical language model SLM directly from our interpretation grammar and compare recognition performance of this model against a speech recognition grammar compiled from the same GF interpretation grammar. The results show a relative Word Error Rate WER reduction of 37 for the SLM derived from the interpretation grammar while maintaining a low in-grammar WER comparable to that associated with the speech recognition grammar. From this starting point we try to improve our artificially generated model by interpolating it with different corpora achieving great reduction in perplexity and 8 relative recognition improvement. 1 Introduction Ideally when building spoken dialogue systems we would like to use a corpus of transcribed dialogues corresponding to the specific task of the dialogue system in order to build a statistical language model SLM . However it is rarely the case that such a corpus exists in the early stage of the development of a dialogue system. Collecting such a corpus and transcribing it is very timeconsuming and delays the building of the actual dialogue system. An approach taken both in dialogue systems and dictation applications is to first write an interpretation grammar and from that generate an artificial corpus which is used as training corpus for the SLM Raux et al 2003 Pakhomov et al 2001 Fosler-Lussier Kuo 2001 . These models obtained from grammars are not as good as the ones built from real data as the estimates are artificial lacking a real distribution. However it is a quick way to get a dialogue system working with an SLM. .

• Báo cáo khoa học
• Generating statistical language models
• interpretation grammars
• dialogue systems
• 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