ISCA Archive Interspeech 2008
ISCA Archive Interspeech 2008

Speaker verification with non-audible murmur segments by combining global alignment kernel and penalized logistic regression machine

Hideki Okamoto, Tomoko Matsui, Hiromichi Kawanami, Hiroshi Saruwatari, Kiyohiro Shikano

We investigate a novel method for speaker verification with nonaudible murmur (NAM) segments. NAM is recorded using a special microphone placed on the neck and is hard for other people to hear. We have already reported a method based on a support vector machine (SVM) using NAM segments to use a keyword phrase effectively. To further exploit keyword-specific features, we introduce a global alignment (GA) kernel and penalized logistic regression machine (PLRM). In the experiments using NAM from 55 speakers, our method achieved an error reduction rate of roughly 60% compared with the SVM-based method using a polynomial kernel.


doi: 10.21437/Interspeech.2008-398

Cite as: Okamoto, H., Matsui, T., Kawanami, H., Saruwatari, H., Shikano, K. (2008) Speaker verification with non-audible murmur segments by combining global alignment kernel and penalized logistic regression machine. Proc. Interspeech 2008, 1369-1372, doi: 10.21437/Interspeech.2008-398

@inproceedings{okamoto08_interspeech,
  author={Hideki Okamoto and Tomoko Matsui and Hiromichi Kawanami and Hiroshi Saruwatari and Kiyohiro Shikano},
  title={{Speaker verification with non-audible murmur segments by combining global alignment kernel and penalized logistic regression machine}},
  year=2008,
  booktitle={Proc. Interspeech 2008},
  pages={1369--1372},
  doi={10.21437/Interspeech.2008-398}
}