Temporal and Spectral Processing Methods for Processing of Degraded Speech: A Review <s> Temporal Envelope Filtering <s> Starting from a known relation between modulation transfer function (of a room) and speech intelligibility, we tried to enhance speech corrupted by reverberation or noise by suitably filtering the envelope (power) signals in critical frequency bands. Two methods based on FFT-overlap-adding and onlinear prediction, respectively, have been developed. Linear envelope filtering was not successful for neither pre- nor postprocessing, even though the objective SNR was improved. However, inserting a logarithmic nonlinearity or, better, a logarithmic one becoming linear at high levels, did raise intelligibility in the presence of noise when the filter effected strong compression at very low and no change or expansion at higher modulation frequencies. Since noise masking can serve as a model for recruitment in sensorineural hearing impairment, the method might be used in future hearing aids. <s> BIB001 </s> Temporal and Spectral Processing Methods for Processing of Degraded Speech: A Review <s> Temporal Envelope Filtering <s> The authors explore speech dereverberation techniques whose principle is the recovery of the envelope modulations of the original (anechoic) speech. Based on their previous experience with such kind of processing for additive noise reduction applications, they apply a data designed filter-bank technique to the reverberant speech. Comparing their results with other works they discuss the effectiveness and limitations of this type of approaches. <s> BIB002 </s> Temporal and Spectral Processing Methods for Processing of Degraded Speech: A Review <s> Temporal Envelope Filtering <s> A basic method for restoring the power envelope from a reverberant signal was proposed by Hirobayashi et al. This method is based on the concept of the modulation transfer function (MTF) and does not require that the impulse response of an environment be measured. However this basic method has the following problems: (i) how to precisely extract the power envelope from the observed signal; (ii) how to determine the parameters of the impulse response of the room acoustics; and (iii) a lack of consideration as to whether the MTF concept can be applied to a more realistic signal. This paper improves this basic method with regard to these problems in order to extend this method as a first step towards the development for speech applications. We have carried out 1,500 simulations for restoring the power envelope from reverberant signals in which the power envelopes are three types of sinusoidal, harmonics, and band-limited noise and the carriers are white noise, to evaluate our improved method with regard to (i) and (ii). We then have carried out the same simulations in which the carriers are two types of carrier of white noise or harmonics with regard to (iii). Our results have shown that the improved method can adequately restore the power envelope from a reverberant signal and will be able to be applied for speech envelope restoration. <s> BIB003
Various single microphone algorithms are proposed using modulation transfer function (MTF) of speech BIB002 . According to this method the envelope of the reverberant speech can be approximated by the convolution of the clean speech signal, with the envelope of an acoustic impulse response. Therefore, the problem of enhancement reduces to the deconvolution of the room response envelope and the reconstruction of the speech signal. These methods do not require the impulse response of an environment to be measured BIB003 . For example, Langhans and Strube BIB001 proposed an enhancement method, where they appropriately filtered the envelope signals in critical frequency bands based on STFT and linear prediction BIB003 . They used theoretically derived inverse MTF as high pass filtering to reduce the effect of reverberation. Similarly, Aveandano and Hermansky BIB002 attempted to recover the energy envelope of the original speech by applying theoretically derived inverse MTF and an optimum filter trained from clean and reverberant speech BIB003 . To realize this approach, it is assumed that the carrier signal of the speech and the impulse response are white noise. However, these assumptions are not accurate with regard to real speech and reverberation BIB003 . Therefore, this approach has not yet achieved high quality dereverberation.