Paper Info
Title
Development of a Mandarin-English Bilingual Speech Recognition System with Unified Acoustic Models
Abstract
This paper presents our recent work on the development of a grammar-constrained, Mandarin-English bilingual Speech Recognition System (MESRS) for real-world music retrieval. Two of the main difficult issues in handling the bilingual speech recognition for real-world applications are tackled: One is to balance the performance and the complexity of the bilingual speech recognition system; the other is to effectively deal with the matrix language accents in embedded language. A unified bilingual acoustic model, which is derived by the novel Two-pass phone-clustering method based on the Confusion Matrix (TCM), is developed to solve the first problem. To deal with the second problem, several nonnative model modification approaches are investigated on the unified acoustic models. Compared to the existing log-likelihood phone-clustering method, the proposed TCM method with effective incorporation of limited amounts of nonnative adaptation data and adaptive modification, relatively reduces the Phrase Error Rate (PER) by 10.9% for nonnative English phrases and the PER on Mandarin phrases decreases favorably, and besides, the recognition rate for bilingual code-mixing phrases achieves an 8.9% relative PER reduction.
Year
Venue
Keywords
2010
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING
bilingual speech recognition,two-pass phone clustering,confusion matrix,non-native adaptation,model retraining
Field
DocType
Volume
Domain-specific language,Confusion matrix,Multilingualism,Computer science,Word error rate,Phrase,Speech recognition,Grammar,Natural language processing,Artificial intelligence,Mandarin Chinese,Acoustic model
Journal
26
Issue
ISSN
Citations 
4
1016-2364
1
PageRank 
References 
Authors
0.43
9
3
Name
Order
Citations
PageRank
Qingqing Zhang110214.76
Jielin Pan24418.04
Yonghong Yan3656114.13