TAILIEUCHUNG - Báo cáo khoa học: "AN AUTOMATIC SPEECH RECOGNITION SYSTEM FOR ITALIAN LANGUAGE"

An automatic speech recognition system for Italian language has been developed at IBM Italy Scientific Center in Rome. It is able to recognize in real time natural language sentences, composed with words from a dictionary of 6500 items, dictated by a speaker with short pauses among them. The system is speaker dependent, before using it the speaker has to perform the training stage reading a predefined text 15-20 minutes long. It runs on an architecture composed by an IBM 3090 mainframe and a PC/AT based workstation with signal processing equipments. . | AN AUTOMATIC SPEECH RECOGNITION SYSTEM FOR HIE ITALIAN LANGUAGE Paolo D Orta Marco Ferretti Alessandro Martclli Stefano Scarci IBM Rome Scientific Center via Giorgione 159 ROME Italy ABSTRACT An automatic speech recognition system for Italian language has been developed at IBM Italy Scientific Center in Rome. It is able to recognize in real time natural language sentences composed with words from a dictionary of 6500 items dictated by a speaker with short pauses among them. The system is speaker dependent before using it the speaker has to perform the training stage reading a predefined text 15-20 minutes long. It runs on an architecture composed by an IBM 3090 mainframe and a PC AT based workstation with signal processing equipments. PROBABILISTIC APPROACH The problem of recognizing human voice is approached in a probabilistic manner. Let w VVỊ be a sequence of n words and let A be the acoustic information extracted from the speech signal from which-the system will try to identify the pronounced words. P w IA _indicates the probability that the the sequence of words has been spoken once we observe the acoustic string A produced at the end of the signal processing stage. The most probable sequence of word given A is that maximizing P w IA . Through Bayes formula A . _ _ - Pl A I W P W P W A max P w IA max y v 2 - - P A PịA I W denotes the probability that__the sequence of words w will produce the acoustic_string_ l P W is the a priori probability of word string w P A is the probability of acoustic string A. To find the word sequence which maximizes the third term in the preceding equation it is sufficient to -find the sequence which maximizes the numerator P A is in fact clearly not dependent on any w. Then the recognition task can be decomposed in these problems 1. perform an acoustic processing able to extract from the speech signal an information A representative of its acoustic features and at the same time adequate for a statistical analysis 2. create an

• Báo cáo khoa học
• AN AUTOMATIC SPEECH RECOGNITION SYSTEM
• ITALIAN LANGUAGE
• Long Papers
• scientific reports
• model language
• process natural language
• Vietnamese automatic speech recognition
• Transcription system
• Force alignment procedure
• Discriminative training
• State of the art Vietnamese ASR
• 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
• 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