Fast convergence speech source separation in reverberant acoustic environment

Three significant enhancements to time-domain adaptive decorrelation filtering (ADF) are proposed for effective separation and recognition of simultaneous speech sources in reverberant room conditions. The methods include whitening filtering on cochannel speech prior to ADF to improve condition of adaptive estimation, a novel block-iterative implementation of ADF to speed up convergence rate, and an integration of multiple ADF outputs through optimal post-filtering. Experimental data were generated by convolving TIMIT speech with acoustic path impulse responses measured in a real acoustic environment, with a 2m microphone-source distance and an initial target-to-interference ratio of about 0 dB. The proposed methods are shown to have speeded up the convergence rate of ADF to a level feasible for online applications, and they have significantly improved target-to-interference ratio and accuracy of phone recognition.