A Hybrid Method of Noise Robust Speech Recognition Based on Fractional Spectral Subtraction and Perceptual Linear Preditive

By combining Fractional Spectral Subtraction (FSS) with Perceptual Linear Predictive (PLP), a hybrid method of noise robustness speech recognition isinvestigated in this paper. This method uses FSS for noisy speech to reduce noise components in the fractional Fourier domain. According to the results ofcomputing Itakura distance and Mean Square Error (MSE), an approximate optimal fractional order is then obtained by comparing the difference betweenthem. Perceptual Linear Predictive Cepstral Coefficients (PLPCC) is finally computed for the enhanced speech in terms of the above obtained order.It is shown that this hybrid method performs better compared with conventional spectral subtraction and PLPCC for digits speech recognition experiments. Moreover, this method denotes good noise robustness when noise levels increases.