DocumentCode :
302323
Title :
Context-dependent acoustic models for Chinese speech recognition
Author :
Ma, Bin ; Huang, Taiyi ; Xu, Bo ; Zhang, Xijun ; Qu, Fei
Author_Institution :
Inst. of Autom., Acad. Sinica, Beijing, China
Volume :
1
fYear :
1996
fDate :
7-10 May 1996
Firstpage :
455
Abstract :
Selecting good speech units and building precise acoustic models on these units are basic problems for HMM speech recognition systems. In this paper, we review some distinguished phonetic features of the Chinese language and show how these features could be considered for getting a better solution of speech units selection and acoustic model building. The initials and finals are suggested to be the recognition units. Several experiments have been carried out to find those proper acoustic models which can represent the co-articulation among initials and finals more accurately and give a higher recognition rate. Results of recognition error rate under different acoustic models are given and some comparisons are made. Experiments show that not only the intra-syllable context-dependent acoustic models but also the inter-syllable acoustic models are necessary for reducing recognition error rate of words and continuous speech recognition. Experiments also show the tone-pattern information is important for accurate syllable recognition
Keywords :
natural languages; speech recognition; Chinese speech recognition; HMM speech recognition; acoustic models; co-articulation; context-dependent acoustic models; continuous speech recognition; error rate; finals; initials; inter-syllable acoustic models; intra-syllable context-dependent acoustic models; phonetic features; precise acoustic models; speech units; syllable recognition; tone-pattern information; word; Automation; Buildings; Context modeling; Error analysis; Hidden Markov models; Natural languages; Pattern recognition; Speech recognition; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
ISSN :
1520-6149
Print_ISBN :
0-7803-3192-3
Type :
conf
DOI :
10.1109/ICASSP.1996.541131
Filename :
541131
Link To Document :
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