Comparative Studies of Single-Channel Speech Enhancement Techniques

Several speech enhancement techniques like Spectral Subtraction, MMSE, Log-MMSE, $ \rbeta $ beta-order MMSE, adaptive $ \rbeta $ beta-order MMSE and compressive sensing methods are developed worldwide. Scientists, engineers and researchers have implemented, evaluated and tested all methods individually with the different speech corpus. However, we found few articles on comparative studies of various speech enhancement techniques. In the present paper, several speech enhancement techniques have been studied, and their performance in terms of speech quality measures is compared objectively and subjectively. The results have been evaluated not only through speech quality measures but also in terms of waveform and spectrogram for speech enhancement applications. For this, MATLAB is used for the simulation of all methods. After getting the enhanced speech signals, we evaluated their enhanced speech signals of the methods. Results in terms of objective evaluation parameters indicated that the adaptive $ \rbeta $ beta-order MMSE-based method produces good-quality speech signals compared to the other methods. Also, we evaluated their enhanced speech signals using a listening test, i.e. subjective evaluation. In the subjective quality test through mean opinion score (using the listening test), the performance of the adaptive $ \rbeta $ beta-order MMSE method and GOMP are equal. In the case of waveform and spectrogram, the visualisation of enhanced speech signal obtained from GOMP-based compressive algorithms is very close to clean speech signal.