9th Annual Conference of the International Speech Communication Association

Brisbane, Australia
September 22-26, 2008

Speaker Verification with Non-Audible Murmur Segments by Combining Global Alignment Kernel and Penalized Logistic Regression Machine

Hideki Okamoto (1), Tomoko Matsui (2), Hiromichi Kawanami (1), Hiroshi Saruwatari (1), Kiyohiro Shikano (1)

(1) NAIST, Japan; (2) ISM, Japan

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.

Full Paper

Bibliographic reference.  Okamoto, Hideki / Matsui, Tomoko / Kawanami, Hiromichi / Saruwatari, Hiroshi / Shikano, Kiyohiro (2008): "Speaker verification with non-audible murmur segments by combining global alignment kernel and penalized logistic regression machine", In INTERSPEECH-2008, 1369-1372.