Felicia Lim

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A novel approach is proposed for robust multichannel dereverberation in the presence of system identification error (SIEs), based on channel shortening. A mathematical link is derived between the well known multiple-input/output inverse theorem (MINT) algorithm and channel shortening. The relaxed multichannel least squares (RMCLS) algorithm is then proposed(More)
Reverberation is a process that distorts a wanted signal and impairs perceived speech quality. In the context of multichannel derever-beration, channel-based methods and beamforming are two common approaches. Channel-based methods such as the multiple in-put/output inverse theorem (MINT) can provide perfect derever-beration provided the exact acoustic(More)
This paper presents a novel algorithm for robust multichannel dere-verberation in the presence of system identification errors with the specific aim of avoiding colouration of the equalized signal. Our proposed algorithm is based upon the technique of channel shortening, which targets only the late taps of the room impulse response. Within the framework of(More)
It is well known that blind system identification (BSI) algorithms misconverge in the presence of noise and that applications relying on such channel estimates must be designed to be robust to these blind system identification errors (BSIEs). However, there is currently no generalized model of BSIEs in the literature and instead, white Gaussian noise (WGN)(More)
Signals captured by microphone arrays provide spatial diversity that can be exploited by multichannel processing algorithms to suppress noise and reverberation. Beamforming is a class of approaches that treats the problem with respect to the spatial location of wanted and competing sources, leveraging properties of propagation of waves in free space. A(More)
Multichannel equalization of acoustic impulse responses (AIRs) is an important approach for dereverberation. Since AIRs are inevitably estimated with system identification error (SIE), it is necessary to develop equalization designs that are robust to such SIE, in order for dereverberation processing to be beneficial. We present here a novel subband(More)
Reverberation time is an important parameter for characterizing acoustic environments. It is useful in many applications including acoustic scene analysis, robust automatic speech recognition and dereverberation. Given knowledge of the acoustic impulse response, reverberation time can be measured using Schroeder's backward integration method. Since it is(More)
Multichannel equalization algorithms which are robust to system identification errors (SIEs) are important for practical speech dereverberation. We present an equalizer employing variable relaxation within the framework of the relaxed multichannel least squares (RMCLS) algorithm in frequency subbands. We show that varying the relaxation of constraints in(More)
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