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http://dx.doi.org/10.6109/jkiice.2015.19.1.61

Target Speech Detection Using Gaussian Mixture Model of Frequency Bandwise Power Ratio for GSC-Based Beamforming  

Chang, Hyungwook (Department of Electronics Engineering, Gyeongsang National University)
Kim, Youngil (Department of Electronics Engineering, Gyeongsang National University)
Jeong, Sangbae (Department of Electronics Engineering, Gyeongsang National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.19, no.1, 2015 , pp. 61-68 More about this Journal
Abstract
Noise reduction is necessary to compensate for the degradation of recognition performance by various types of noises. Among many noise reduction techniques using microphone array, generalized sidelobe canceller (GSC) has been widely applied to reduce nonstationary noises. The performance of GSC is directly affected by its adaptation mode controller (AMC). That is, accurate target speech detection is essential to guarantee the sufficient noise reduction in pure noise intervals and the less distortion in target speech intervals. Thus, this paper proposes an improved AMC design technique in which the power ratio of the output of fixed beamforming to that of blocking matrix is calculated frequency bandwise and probabilistically modeled by mixture Gaussians for each class. Experimental results show that the proposed algorithm outperforms conventional AMCs in receiver operating curves (ROC) and output SNRs.
Keywords
noise reduction; microphone array; generalized sidelobe canceller;
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