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MMSE STSA estimator with nonstationary noise estimation based on ICA for high-quality speech enhancement

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4 Author(s)
Ryoi Okamoto ; Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma-shi, 630-0192, JAPAN ; Yu Takahashi ; Hiroshi Saruwatari ; Kiyohiro Shikano

In this paper, we propose a new blind speech extraction method consisting of a minimum mean-square error short-time spectral amplitude (MMSE STSA) estimator and noise estimation based on independent component analysis (ICA). First, we perform a computer simulation using the artificial noise whose stationarity could be controlled parametrically, and the obtained results indicate that the proposed method is superior to conventional methods, such as blind spatial subtraction array (BSSA) and the original MMSE STSA estimator under the non-point-source and nonstationary noise condition. Finally, we conduct an experiment in an actual railway-station environment, and objective and subjective evaluations to confirm the advantage of the proposed method in the real world.

Published in:

2010 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

14-19 March 2010