Title
Robust several-speaker speech recognition with highly dependable online speaker adaptation and identification
Abstract
The currently adaptive mechanisms adapt a single acoustic model for a speaker in speaker-independent speech recognition system. However, as more users use the same speech recognizer, single acoustic model adaptation leads to negative adaptation upon switching between users. Such a situation is problematic (undependable adaptation). This paper, considering the situation of a smart home or an office with staff members, presents the speaker-specific acoustic model adaptation based on a multi-model mechanism, to solve the problem of undependable adaptation. First, the identification of the current speaker is confirmed using the SVM classifier, then the corresponding acoustic parameters are extracted and integrated with the speaker-independent acoustic model to yield the speaker-dependent acoustic model and speech recognition accuracy then be promoted for the current speaker. To provide dependable adaptation data to achieve online positive speaker adaptation, a mechanism that measures confidence score is designed to verify each recognition result and determined whether it can be an adaptation datum. The experimental results indicate that the proposed system can effectively increase the average speech recognition accuracy from 62% to 85%. Thus, the proposed system can achieve robust several-speaker speech recognition with highly dependable online speaker adaptation and identification.
Year
DOI
Venue
2011
10.1016/j.jnca.2010.08.007
J. Network and Computer Applications
Keywords
DocType
Volume
speaker-specific acoustic model adaptation,single acoustic model adaptation,online positive speaker adaptation,dependable adaptation data,adaptation datum,proposed system,undependable adaptation,negative adaptation,robust several-speaker speech recognition,dependable online speaker adaptation,current speaker
Journal
34
Issue
ISSN
Citations 
5
Journal of Network and Computer Applications
10
PageRank 
References 
Authors
0.78
20
4
Name
Order
Citations
PageRank
Po-Yi Shih1365.61
Po-chuan Lin2475.73
Jhing-fa Wang3982114.31
Yuan-Ning Lin4131.56