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  1. Journal of Computer Science and Technology
  2. Journal of Computer Science and Technology : Volume 21
  3. Journal of Computer Science and Technology : Volume 21, Issue 1, January 2006
  4. A Dialectal Chinese Speech Recognition Framework
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Journal of Computer Science and Technology : Volume 32
Journal of Computer Science and Technology : Volume 31
Journal of Computer Science and Technology : Volume 30
Journal of Computer Science and Technology : Volume 29
Journal of Computer Science and Technology : Volume 28
Journal of Computer Science and Technology : Volume 27
Journal of Computer Science and Technology : Volume 26
Journal of Computer Science and Technology : Volume 25
Journal of Computer Science and Technology : Volume 24
Journal of Computer Science and Technology : Volume 23
Journal of Computer Science and Technology : Volume 22
Journal of Computer Science and Technology : Volume 21
Journal of Computer Science and Technology : Volume 21, Issue 6, November 2006
Journal of Computer Science and Technology : Volume 21, Issue 5, September 2006
Journal of Computer Science and Technology : Volume 21, Issue 4, July 2006
Journal of Computer Science and Technology : Volume 21, Issue 3, May 2006
Journal of Computer Science and Technology : Volume 21, Issue 2, March 2006
Journal of Computer Science and Technology : Volume 21, Issue 1, January 2006
Recent Advances in Evolutionary Computation
P-Tree Structures and Event Horizon: Efficient Event-Set Implementations
An Improved Algorithm for Finding the Closest Pair of Points
Revisiting the Meaning of Requirements
Remove Irrelevant Atomic Formulas for Timed Automaton Model Checking
Efficient Incremental Maintenance for Distributive and Non-Distributive Aggregate Functions
A Workflow Process Mining Algorithm Based on Synchro-Net
TCP Issues in Mobile Ad Hoc Networks: Challenges and Solutions
Pseudorandomness of Camellia-Like Scheme
A Near-Optimal Optimization Algorithm for Link Assignment in Wireless Ad-Hoc Networks
Communication Between Speech Production and Perception Within the Brain—Observation and Simulation
A Dialectal Chinese Speech Recognition Framework
Image Region Selection and Ensemble for Face Recognition
Quaternion Diffusion for Color Image Filtering
Novel Cluster Validity Index for FCM Algorithm
A Test Approach for Look-Up Table Based FPGAs
ACO-Steiner: Ant Colony Optimization Based Rectilinear Steiner Minimal Tree Algorithm
Journal of Computer Science and Technology : Volume 20
Journal of Computer Science and Technology : Volume 19
Journal of Computer Science and Technology : Volume 18
Journal of Computer Science and Technology : Volume 17
Journal of Computer Science and Technology : Volume 16
Journal of Computer Science and Technology : Volume 15
Journal of Computer Science and Technology : Volume 14
Journal of Computer Science and Technology : Volume 13
Journal of Computer Science and Technology : Volume 12

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A Dialectal Chinese Speech Recognition Framework

Content Provider SpringerLink
Author Li, Jing Zheng, Thomas Fang Byrne, William Jurafsky, Dan
Copyright Year 2006
Abstract A framework for dialectal Chinese speech recognition is proposed and studied, in which a relatively small dialectal Chinese (or in other words Chinese influenced by the native dialect) speech corpus and dialect-related knowledge are adopted to transform a standard Chinese (or Putonghua, abbreviated as PTH) speech recognizer into a dialectal Chinese speech recognizer. Two kinds of knowledge sources are explored: one is expert knowledge and the other is a small dialectal Chinese corpus. These knowledge sources provide information at four levels: phonetic level, lexicon level, language level, and acoustic decoder level. This paper takes Wu dialectal Chinese (WDC) as an example target language. The goal is to establish a WDC speech recognizer from an existing PTH speech recognizer based on the Initial-Final structure of the Chinese language and a study of how dialectal Chinese speakers speak Putonghua. The authors propose to use context-independent PTH-IF mappings (where IF means either a Chinese Initial or a Chinese Final), context-independent WDC-IF mappings, and syllable-dependent WDC-IF mappings (obtained from either experts or data), and combine them with the supervised maximum likelihood linear regression (MLLR) acoustic model adaptation method. To reduce the size of the multi-pronunciation lexicon introduced by the IF mappings, which might also enlarge the lexicon confusion and hence lead to the performance degradation, a Multi-Pronunciation Expansion (MPE) method based on the accumulated uni-gram probability (AUP) is proposed. In addition, some commonly used WDC words are selected and added to the lexicon. Compared with the original PTH speech recognizer, the resulting WDC speech recognizer achieves 10–18% absolute Character Error Rate (CER) reduction when recognizing WDC, with only a 0.62% CER increase when recognizing PTH. The proposed framework and methods are expected to work not only for Wu dialectal Chinese but also for other dialectal Chinese languages and even other languages.
Starting Page 106
Ending Page 115
Page Count 10
File Format PDF
ISSN 10009000
Journal Journal of Computer Science and Technology
Volume Number 21
Issue Number 1
e-ISSN 18604749
Language English
Publisher Kluwer Academic Publishers
Publisher Date 2006-01-01
Publisher Place Boston
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword dialectal Chinese speech recognition initial or final (IF) IF-mapping rule pronunciation modeling small quantity of speech data Theory of Computation Information Systems Applications (incl.Internet) Artificial Intelligence (incl. Robotics) Computer Science Software Engineering Data Structures, Cryptology and Information Theory
Content Type Text
Resource Type Article
Subject Theoretical Computer Science Computational Theory and Mathematics Computer Science Applications Software Hardware and Architecture
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