Eigenvoice based speaker adaptation method is known to be very effective tool for rapid speaker adaptation. Stochastic matching approach is also known as a powerful method to reduce the mismatch between training and test environments. In this paper, we simultaneously applied two methods for speaker adaptation and environment compensation space based on the eigenvoice adaptation framework. In experiments for vocabulary-independent word recognition task with supervised mode adaptation, the proposed method shows higher performance improvement than conventional eigenvoice adaptation method with a small adaptation data. We obtained 19~30% relative improvement with only single adaptation utterance and obtained 37% relative improvement with 50 adaptation utterances by proposed method.
Cite as: Kim, H.S., Song, H.J. (2004) Simultaneous estimation of weights of eigenvoices and bias compensation vector for rapid speaker adaptation. Proc. Interspeech 2004, 2945-2948, doi: 10.21437/Interspeech.2004-22
@inproceedings{kim04b_interspeech,
author={Hyung Soon Kim and Hwa Jeon Song},
title={{Simultaneous estimation of weights of eigenvoices and bias compensation vector for rapid speaker adaptation}},
year=2004,
booktitle={Proc. Interspeech 2004},
pages={2945--2948},
doi={10.21437/Interspeech.2004-22}
}