Speaker Adaptation Method Based on Eigenphone Speaker Subspace for Speech Recognition

Qu Dan; Zhang Wen-lin

doi:10.11999/JEIT141264

Volume 37 Issue 6

Jun. 2015

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Article Navigation > Journal of Electronics & Information Technology > 2015 > 37(6): 1350-1356

Qu Dan, Zhang Wen-lin. Speaker Adaptation Method Based on Eigenphone Speaker Subspace for Speech Recognition[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1350-1356. doi: 10.11999/JEIT141264

Citation:

Qu Dan, Zhang Wen-lin. Speaker Adaptation Method Based on Eigenphone Speaker Subspace for Speech Recognition[J]. Journal of Electronics & Information Technology, 2015, 37(6): 1350-1356. doi: 10.11999/JEIT141264

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Speaker Adaptation Method Based on Eigenphone Speaker Subspace for Speech Recognition

doi: 10.11999/JEIT141264

Qu Dan¹,
Zhang Wen-lin¹

Received Date: 2014-09-30
Rev Recd Date: 2014-12-29
Publish Date: 2015-06-19

Abstract

Abstract

The eigenphone speaker adaptation method performs well when the amount of adaptation data is sufficient. However, it suffers from severe over-fitting when insufficient amount of adaptation data is provided. A speaker adaptation method based on eigenphone speaker subspace is proposed to overcome this problem. Firstly, a brief overview of the eigenphone speaker adaptation method is presented in case of Hidden Markov Model-Gaussian Mixture Model (HMM-GMM) based speech recognition system. Secondly, speaker subspace is introduced to model the inter-speaker correlation information among different speakers eigenphones. Thirdly, a new speaker adaptation method based on eigenphone speaker subspace is derived from estimation of a speaker dependent coordinate vector for each speaker. Finally, a comparison between the new method and traditional speaker subspace based method is discussed in detail. Experimental results on a Mandarin Chinese continuous speech recognition task show that compared with original eigenphone speaker adaptation method, the performance of the eigenphone speaker subspace method can be improved significantly when insufficient amount of adaptation data is provided. Compared with eigenvoice method, eigenphone speaker subspace method can save a great amount of storage space only at the expense of minor performance degradation.
- Speech signal processing,
- Speaker adaptation,
- Eigenphone,
- Eigenphones speaker subspace,
- Low-rank constraint,
- Eigenvoice

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References(16)

References

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