An Immittance Spectral Frequency Parameters Quantization Algorithm Based on Gaussian Mixture Model
Xiaochen Wang, Zhang Yong, Ruimin Hu, Du Xi · 2009
An efficient Immittance Spectral Frequency (ISF) parameters quantization algorithm is proposed based on the Gaussian mixture model (GMM). The basic idea of the algorithm is the use of GMM to send the ISF parameters into M Gaussian clusters, ISF parameters are quantized by a Gaussian lattice vector quantizer corresponding to that Gaussian clustering, and the minimal spectral distortion value among the M quantized values is selected at last. In the design of Gaussian lattice vector quantizer, the optimal bit allocation algorithm is proposed based on the rate-distortion theory. The results show that the ISF parameters could be transparently quantized at 42 bit/frame, which saves 3 bits and reduce 58% of the storage compared with the Split - Multi-Stage Vector Quantization (S-MSVQ) algorithm of AMR-WB(G.722.2).