Experimental study on noise pre-processing for a low bit rate speech coder
Wenhua Shi, Xiongwei Zhang, Xia Zou, Xiaodong Song · 2016
This paper focuses on the quality of speech coding parameters extraction under noisy and clean conditions. The influence of speech enhancement on the quality of extracted parameters for a low bit rate speech coder is addressed. MELP vocoder is used to estimate three parameters: the fundamental frequency, voicing and linear prediction coefficients. De-noising methods in MELPe vocoder and SMV are adopted as preprocessor under different noise environment separately. Pitch accuracy rate, voicing decision error rate and average spectral distortion are employed to quantitatively evaluate the quality and intelligibility improvements for the degraded speech with and without noise pre-processing system. The experimental results show that noise pre-processing can provide improvement in parameter estimation especially in low SNR. MELPe speech enhancement algorithm has better parameter extraction performance than SMV. The research will be helpful in designing specific noise pre-processing algorithm for low bit rate parametric coding.