TAILIEUCHUNG - Báo cáo khoa học: "A Finite-Slate Parser for Use in Speech Recognition"

This paper is divided into two parts. 1 The first section motivates the application of finite-state parsing techniques at the phonetic level in order to exploit certain classes or" contextual constraints. -In the second section, the parsing framework is extended in order to account ['or 'feature spreading' (i:.g., agreement and co-articulation) in a natural way. | A Finite-State Parser for Use in Speech Recognition Kenneth w. Church NE43-307 Massachusetts Institute ofTcchnology Cambridge MA. 02139 This paper is divided into two Ihc first section motivates the application of finite-state parsing techniques at the phonetic level in order to exploit certain classes of contextual constraints. In the second section the parsing framework is extended in order to account for feature spreading . agreement and co-articulation in a natural way. 1. Parsing at the Phonetic Level It is well known that phonemes have different acoustic phonctic realizations depending on the context For example die phoneme ư is typically realized with a different allophone phonetic variant in syllable initial position than in syllabic final position. In syllabic initial position . Tom t is almost always released with a strong burst of energy and aspirated with h-likc noise whereas in syllable final position . cat zt is often unrelcascd and unaspirated. It is common practice in speech research to distinguish acoustic phonetic properties that vary a great deal with context . release and aspiration from those that are relatively invariant to context . place manner and voicing .2 In the past the emphasis has been on invariants allophonic variation is traditionally seen as problematic for recognition. 1 In most systems for sentence recognition such modifications must be viewed as a kind of noise that makes it more difficult to hypothesize lexical candidates given an input phonetic transcription. To see that this must be the case we note that each phonological rule in an example to be presented below 1. This research was supported in part by die National Institutes of I Icalth Grant No. 1 rot I M 03374-01 and 03374-02 from the National Library of .Medicine. 2. Place refers IO the location of Ute constriction in the vocal trace lixamples include labial al the lips Zp. b. f. V. mZ. velar Zk. g. T Z. dental at the teeth Zs. z. 1. d. I nZ and .

• Báo cáo khoa học
• A Finite Slate Parser
• Use in Speech Recognition
• Kenneth W
• Church
• 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