Multimicrophone speech dereverberation with noise for hand - free communication

Abstract

Revcrberation is one of thc primary factors that dcgrade the quality of speech signals whcn recorded by a distant microphonc in order to facilitate hands-frce communication. Undoing the effect of reverberation is still a challenging problem especially when additive noise and time-varying acoustic channels arc considered. In this dissertation, several multimicrophone dcreverbcration techniqucs are developed that can dereverberatc the rccordcd specch as well as improve the signal-ta-noise ratio (SNR) considering a practical acoustic environment. The methods are based on the adaptive estimation of the long acoustic impulse responses (AIRs) using the multichannel LMS (MCLMS) algorithm. Although the MCLMS algorithm is attractive for its simplicity and computational efficiency, it suffers from slow convergence rate, step-size ambiguity, and last but not the least, lack of robustness in the presence of noise. A variable-step-sizc frequency-domain MCLMS algorithm is proposcd that can ensure stability and optimal convergence speed both in the noise-frcc and noisy conditions. To improvc the noisc-robustness of thc class of MCLMS algorithms, two novcl solutions, namely, excitation-driven MCLMS and spcctrally constraint MCLMS algorithms are proposed that can successfully estimate thc long AIRs with reasonable accuracy. Based on adaptive cstimation of the AIRs, two different dereverberation techniques are proposed. In the first approach, derevcrberation is achieved by suppressing the late reverberation using channel shortening technique and the SNR is improved by delay-and-sum beamforming. The proposed shortening algorithm is also optimized so that it makes a trade-off between shortening performance and spectral distortion in the dcreverberated speech. In the sccond approach, the power of the speech components in the receivcd microphone signals are first enhanced by an eigenfilter and then a block-adaptive zero-forcing equalizer is employed to eliminate the channel distortion introduccd by the AIRs and cigenfilter. The cigenfilter is cfficiently estimated avoiding the tedious Cholesky factorization and it also resists spectral nulls so that noise amplification is mitigated at the output of the zero-forcing equalizer. Extensive experiments are conducted, using both simulated and real reverberant acoustic channels, which demonstrate that the proposed methods can offer better speech quality and SNR improvement as compared to the state-of-the-art dcreverberation techniques.