Paper Info
Title
A Novel Approach In Continuous Speech Recognition For Vietnamese, An Isolating Tonal Language
Abstract
This paper proposes a new approach for the integration of the Vietnamese language characteristics into a Large Vocabulary Continuous Speech Recognition System (LVCSR) which was built for some European languages. Firstly, a new module of tone recognition using Hidden Markov model was constructed. Secondly, several methods were applied to transform a text corpus of monosyllabic words into text corpus of polysyllabic words and a statistical language model of polysyllabic words was built by using the new text corpus. Finally, all the knowledge has been included in the LVCSR system so that this system can be adapted for Vietnamese. Experiments are made on the VNSPEECHCORPUS. The results show that the accuracy of Vietnamese recognition system was increased, 46% of relative reduction of the word error rate is obtained by using Vietnamese language characteristics.
Year
Venue
Keywords
2008
INTERSPEECH 2008: 9TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2008, VOLS 1-5
speech recognition, Vietnamese speech, tone recognition, statistic language model, polysyllabic words
Field
DocType
Citations 
Recognition system,Computer science,Word error rate,Text corpus,Speech recognition,Continuous speech recognition system,Artificial intelligence,Natural language processing,Vietnamese,Hidden Markov model,Vocabulary,Language model
Conference
3
PageRank 
References 
Authors
0.47
7
4
Name
Order
Citations
PageRank
Hong Quang Nguyen172.38
Pascal Nocera27010.86
Eric Castelli37916.36
Van Loan Trinh4194.62