Temporal and Spectral Processing Methods for Processing of Degraded Speech: A Review <s> Multi-Stage Algorithms <s> The paper presents a new method for dereverberation of speech signals with a single microphone. For applications such as speech recognition, reverberant speech causes serious problems when a distant microphone is used in recording. This is especially severe when the reverberation time exceeds 0.5 s. We propose a method which uses the fundamental frequency (F/sub 0/) of the target speech as the primary feature for dereverberation. This method initially estimates F/sub 0/ and the harmonic structure of the speech signal and then obtains a dereverberation operator. This operator transforms the reverberant signal to its direct signal based on an inverse filtering operation. Dereverberation is achieved without prior knowledge of either the room acoustics or the target speech. Experimental results show that the dereverberation operator estimated from 5240 Japanese word utterances could effectively reduce the reverberation when the reverberation time is longer than 0.1 s. <s> BIB001 </s> Temporal and Spectral Processing Methods for Processing of Degraded Speech: A Review <s> Multi-Stage Algorithms <s> A robust dereverberation method is presented for speech enhancement in a situation requiring adaptation where a speaker shifts his/her head under reverberant conditions causing the impulse responses to change frequently. We combine correlation-based blind deconvolution with modified spectral subtraction to improve the quality of inverse-filtered speech degraded by the estimation error of inverse filters obtained in practice. Our method computes inverse filters by using the correlation matrix between input signals that can be observed without measuring room impulse responses. Inverse filtering reduces early reflection, which has most of the power of the reverberation, and then, spectral subtraction suppresses the tail of the inverse-filtered reverberation. The performance of our method in adaptation is demonstrated by experiments using measured room impulse responses. The subjective results indicated that this method provides superior speech quality to each of the individual methods: blind deconvolution and spectral subtraction. <s> BIB002
During the last decade, several multi-stage algorithms were proposed for the enhancement of reverberant speech. In BIB001 , Nakatani and Miyoshi proposed a system capable of blind dereverberation of one microphone speech, by employing the harmonic structure of speech. In this system, a sinusoidal representation was used to approximate the direct sound in the reverberant environments and adaptive harmonic filters were first employed to estimate the voiced clean speech from the reverberant speech signal. This estimation was then used to derive a dereverberation filter. This method, however, requires accurate estimation of the fundamental frequency from the reverberant speech. Wu and Wang  proposed a two-stage model to enhance reverberant speech. In the first stage, an inverse filter of the room impulse response was estimated, to increase the SRR by maximizing the kurtosis of the LP residual. In the second stage, long term reverberation effects were removed using the spectral subtraction approach. In BIB002 , a hybrid dereverberation method was proposed, which combined correlation based blind deconvolution and modified spectral subtraction to suppress the tail of reverberation and improve the processed speech quality. Inverse filtering reduced the early reflection that constitutes most of the power of the reverberation. Then, the modified spectral subtraction suppressed the tail of the inverse-filtered speech.