Split vector quantizer for wideband ISF parameters based on conditional PDF
Qingqing Liu · Applied science and technology · 2011
Vector quantizing of wideband ISF parameters is an important part of speech coding,and its performance decides the quality of the speech after decoded.A new vector quantization method is proposed for coding the wideband ISF(Immittance Spectral Frequencie)sparameters.In this approach,the conditional PDF(probability density Function)for the parameter vectors of successive source frames is modeled using a GMM(Gaussian mixture mode)l because there exists interframe correlation.In this quantizer,the current frame is classified to choose appropriate quantization codebook based on the previous frame firstly,and then the ISF parameter is quantized using split vector quantization.Experimental results show that this quantization scheme achieves transparent coding at 44bits/frame,and the average spectral distortion is lower than that of traditional split vector quantization.