Temporal and Spectral Processing Methods for Processing of Degraded Speech: A Review <s> Enhancement of Reverberant Speech <s> When a conversation takes place inside a room, the acoustic speech signal is distorted by wall reflections. The room’s effect on this signal can be characterized by a room impulse response. If the impulse response happens to be minimum phase, it can easily be inverted. Synthetic room impulse responses were generated using a point image method to solve for wall reflections. A Nyquist plot was used to determine whether a given impulse response was minimum phase. Certain synthetic room impulse responses were found to be minimum phase when the initial delay was removed. A minimum phase inverse filter was successfully used to remove the effect of a room impulse response on a speech signal. <s> BIB001 </s> Temporal and Spectral Processing Methods for Processing of Degraded Speech: A Review <s> Enhancement of Reverberant Speech <s> In speech communication systems, such as voice-controlled systems, hands-free mobile telephones, and hearing aids, the received microphone signals are degraded by room reverberation, background noise, and other interferences. This signal degradation may lead to total unintelligibility of the speech and decreases the performance of automatic speech recognition systems. In the context of this work reverberation is the process of multi-path propagation of an acoustic sound from its source to one or more microphones. The received microphone signal generally consists of a direct sound, reflections that arrive shortly after the direct sound (commonly called early reverberation), and reflections that arrive after the early reverberation (commonly called late reverberation). Reverberant speech can be described as sounding distant with noticeable echo and colouration. These detrimental perceptual effects are primarily caused by late reverberation, and generally increase with increasing distance between the source and microphone. Conversely, early reverberations tend to improve the intelligibility of speech. In combination with the direct sound it is sometimes referred to as the early speech component. Reduction of the detrimental effects of reflections is evidently of considerable practical importance, and is the focus of this dissertation. More specifically the dissertation deals with dereverberation techniques, i.e., signal processing techniques to reduce the detrimental effects of reflections. In the dissertation, novel single- and multimicrophone speech dereverberation algorithms are developed that aim at the suppression of late reverberation, i.e., at estimation of the early speech component. This is done via so-called spectral enhancement techniques that require a specific measure of the late reverberant signal. This measure, called spectral variance, can be estimated directly from the received (possibly noisy) reverberant signal(s) using a statistical reverberation model and a limited amount of a priori knowledge about the acoustic channel(s) between the source and the microphone(s). In our work an existing single-channel statistical reverberation model serves as a starting point. The model is characterized by one parameter that depends on the acoustic characteristics of the environment. We show that the spectral variance estimator that is based on this model, can only be used when the source-microphone distance is larger than the so-called critical distance. This is, crudely speaking, the distance where the direct sound power is equal to the total reflective power. A generalization of the statistical reverberation model in which the direct sound is incorporated is developed. This model requires one additional parameter that is related to the ratio between the direct sound energy and the sound energy of all reflections. The generalized model is used to derive a novel spectral variance estimator. When the novel estimator is used for dereverberation rather than the existing estimator, and the source-microphone distance is smaller than the critical distance, the dereverberation performance is significantly increased. Single-microphone systems only exploit the temporal and spectral diversity of the received signal. Reverberation, of course, also induces spatial diversity. To additionally exploit this diversity, multiple microphones must be used, and their outputs must be combined by a suitable spatial processor such as the so-called delay and sum beamformer. It is not a priori evident whether spectral enhancement is best done before or after the spatial processor. For this reason we investigate both possibilities, as well as a merge of the spatial processor and the spectral enhancement technique. An advantage of the latter option is that the spectral variance estimator can be further improved. Our experiments show that the use of multiple microphones affords a significant improvement of the perceptual speech quality. The applicability of the theory developed in this dissertation is demonstrated using a hands-free communication system. Since hands-free systems are often used in a noisy and reverberant environment, the received microphone signal does not only contain the desired signal but also interferences such as room reverberation that is caused by the desired source, background noise, and a far-end echo signal that results from a sound that is produced by the loudspeaker. Usually an acoustic echo canceller is used to cancel the far-end echo. Additionally a post-processor is used to suppress background noise and residual echo, i.e., echo which could not be cancelled by the echo canceller. In this work a novel structure and post-processor for an acoustic echo canceller are developed. The post-processor suppresses late reverberation caused by the desired source, residual echo, and background noise. The late reverberation and late residual echo are estimated using the generalized statistical reverberation model. Experimental results convincingly demonstrate the benefits of the proposed system for suppressing late reverberation, residual echo and background noise. The proposed structure and post-processor have a low computational complexity, a highly modular structure, can be seamlessly integrated into existing hands-free communication systems, and affords a significant increase of the listening comfort and speech intelligibility. <s> BIB002
Reverberation affects the quality of speech, in which delayed copies of the speech waveform, called echoes are added to the direct speech. Mathematically, this can be expressed as convolution of the speech signal, with room impulse response BIB001 . That is, where s(n) represents the clean speech, h(n) denotes the room impulse response and * symbolizes the convolution operation. The reverberation is completely characterized by the speaker to receiver room impulse response. This can be divided into three segments: Direct sound, early reflections and late reflections. The first sound that is received without reflection is the direct sound. A little later, the sounds which were reflected off one or more surfaces will be received. These reflected sounds are separated from the direct sound, in both time and direction BIB002 . The reflected sounds form a sound component usually called early reverberation. Early reverberation is actually perceived to reinforce the direct sound and is, therefore, considered useful to speech intelligibility. Late reverberation results from the reflections that arrive with larger delays, after the arrival of the direct sound. They are perceived either as separate echoes or as reverberation and impairing speech intelligibility BIB002 . Various methods for improving the performance in reverberant environments have been proposed. These methods may also be broadly grouped into temporal processing and spectral processing methods. The temporal processing methods obtain the enhancement by processing the reverberant speech in time or cepstral domain and spectral domain processing is accomplished in the frequency domain. Besides these categories, there are several multistage algorithms that have been proposed, which process degraded signal in both time and frequency domains.