Whitening Processing for Blind Separation of Speech Signals

Whitening processing methods are proposed to improve the effectiveness of blind separation of speech sources based on ADF. The proposed methods include preemphasis, prewhitening, and joint linear prediction of common component of speech sources. The effect of ADF filter lengths on source separation performance was also investigated. Experimental data were generated by convolving TIMIT speech with acoustic path impulse responses measured in real acoustic environment, where microphonesource distances were approximately 2 m and initial targetto-interference ratio was 0 dB. The proposed methods significantly speeded up convergence rate, increased target-tointerference ratio in separated speech, and improved accuracy of automatic phone recognition on target speech. The preemphasis and prewhitening methods alone produced large impact on system performance, and combined preemphasis with joint prediction yielded the highest phone recognition accuracy.