Title
Chinese-English bilingual phone modeling for cross-language speech recognition
Abstract
In this paper, three different approaches to Chinese-English bilingual phone modeling are investigated and compared. The first approach is to simply combine Chinese and English phone inventories together without phone sharing across the languages. The second one is to map language-dependent phones to the inventory of the International Phonetic Association (IPA) based on phonetic knowledge to construct the bilingual phone inventory. The third one is to merge the language-dependent phone models by an hierarchical phone clustering algorithm to get a compact bilingual inventory. In the third approach, two distance measures are used to perform the bottom-up clustering. One is the Bhattacharyya distance. The other is the acoustic likelihood distance. Experimental results show that the phone clustering approach outperforms the IPA-based phone mapping approach, and it can also achieve comparable performance to the simple combination of language-dependent phone inventories with fewer model parameters, especially when using acoustic likelihood distance measurement.
Year
DOI
Venue
2004
10.1109/ICASSP.2004.1326136
ICASSP (1)
Keywords
Field
DocType
bhattacharyya distance,speech processing,compact bilingual inventory,pattern clustering,speech recognition,distance measures,maximum likelihood estimation,hierarchical phone clustering,phonetic knowledge,cross-language speech recognition,international phonetic association,bilingual phone inventory,language-dependent phones,ipa,chinese-english bilingual phone modeling,performance,bottom-up clustering,acoustic likelihood distance,clustering algorithms,automatic speech recognition,automation,natural languages,bottom up,loudspeakers
Speech processing,Language speech,Bhattacharyya distance,Computer science,Phone,Natural language processing,Artificial intelligence,Merge (version control),Cluster analysis,Distance measurement,Pattern recognition,Speech recognition,Distance measures
Conference
Volume
ISSN
ISBN
1
1520-6149
0-7803-8484-9
Citations 
PageRank 
References 
12
0.84
9
Authors
3
Name
Order
Citations
PageRank
Shengmin Yu1121.17
Shuwu Zhang212325.97
Bo Xu311127.31