Complex cepstral deconvolution is applied to acoustic dereverberation. It is found that traditional cepstral techniques fail in acoustic dereverberation because segmentation errors in the time domain prevent accurate cepstral computation. An algorithm for speech dereverberation which incorporates a novel approach to the segmentation and windowing procedure for speech is presented. Averaging in the cepstrum is exploited to increase the separation between the speech and impulse response. An estimate of the room impulse response is built, and a least squared error inverse filter is used to remove the estimated impulse response from the reverberant speech. Reduction of reverberation with this technique is demonstrated.< >
Acoustical reverberation has been shown to degrade the intelligibility and naturalness of speech. In this thesis, we discuss the application of cepstral methods to the enhancement of acoustically reverberant speech. We first study previously described cepstral techniques for removal of simple echoes from signals. Our results show that these techniques are not directly applicable to the enhancement of speech of indefinite extent. We next recast these techniques specifically for speech. We propose new segmentation and windowing strategies, in combination with cepstral averaging, to accurately identify the acoustical impulse response. We then consider inverse filtering based on an estimated acoustical impulse response, and find that finite impulse response filters designed according to the least mean squared error criterion provide satisfactory performance. Finally, we synthesize and test an algorithm for enhancement of reverberant speech. Although significant difficulties remain, we feel that our methods offer a substantial contribution to the solution of the reverberant speech enhancement problem.
Speech in rooms is subject to degradation caused by acoustic reverberation. Signal processing techniques to remove reverberation have required multiple microphones or knowledge of the room impulse response. In this paper, complex cepstral deconvolution is applied to acoustic dereverberation. A new ap proach to the segmentation and windowing procedure for speech improves the complex cepstral identification of the reverberant impulse response, and least squares inverse filters are used to remove the estimated impulse response from the reverberant speech. Although complete removal of the impulse response is not possible, reduction of reverberation with this technique is demonstrated.
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