Robust automatic speech recognition using a multi-channel signal separation front-end

A multi-channel signal separation front-end for robust automatic speech recognition under time-varying interference conditions is developed. The speech signals acquired by a dual-channel system are restored by adaptive decorrelation filtering, and then examined by a time-domain or frequency-domain source signal detection technique to determine the active regions of each source signal. The front-end is integrated with an HMM-based speaker-independent continuous speech recognition system by providing the restored signals within the active regions for recognition. Under a simulated room acoustic condition, the overall system shows very promising performance. For the conditions with SNR above-10 dB, the achieved word recognition accuracies are very close to that of the interference-free condition.