|
KMID : 0917520000070010031
|
|
Journal of Speech Sciences
2000 Volume.7 No. 1 p.31 ~ p.37
|
|
|
On Speaker Adaptations with Sparse Training Data for Improved Speaker Verification
|
|
Ahn, Sung Joo
Kang, Sun Mee/Ko, Han Seok
|
|
|
Abstract
|
|
|
This paper concerns effective speaker adaptation methods to solve the over-training problem in speaker verification, which frequently occurs when modeling a speaker with sparse training data. While various speaker adaptations have already been applied to speech recognitaion, these methods have not yet been formally considered in speaker verfication. This paper proposes speaker adaptation methods using a combination of MAP and MLLR adaptations, which are successfully used in speech recognitaion, and applies to speaker verification. Experimental results show that the speaker verification system using a weighted MAP and MLLR adaptation outperforms that of the conventional speaker models without adaptation by a factor of up to 5 times. From these results, we show that the speaker adaptation method achieves significantly better performance even when only small training data is available for speaker verfication.
Keywords: speaker verfication, speaker adaptation, training
|
|
|
KEYWORD
|
|
|
|
|
|
FullTexts / Linksout information
|
|
|
|
|
|
Listed journal information
|
|
|
|
|