Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
Efficient alternatives to the Ephraim and Malah suppression rule for audio signal enhancement
EURASIP Journal on Applied Signal Processing
An evaluation study on speech feature densities for Bayesian estimation in robust ASR
Proceedings of the Third COST 2102 international training school conference on Toward autonomous, adaptive, and context-aware multimodal interfaces: theoretical and practical issues
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In this paper, four STFT based speech enhancement algorithms are proposed. The algorithms enhance speech by estimating its short time spectral amplitude and are combinations of two estimators (MMSE and MAP) with two speech spectral amplitude priors (Gamma and Chi). The proposed priors have a shape parameter a, whose effect on the quality of speech is a focal point of our investigation. Rather than using a priori estimated values of a, we seek those values that maximise the quality of the enhanced speech, in an a posteriori fashion. The performance of the algorithms is first evaluated as a function of the shape parameter a and optimal values are then sought by means of a formal subjective listening test. Finally, the parallel examination of four speech enhancement algorithms offers an insight into the relative importance of the employed priors and estimators, as the proposed algorithms are only different with respect to these two elements.