关键词: 浊音隶属度, 模糊聚类, 矢量量化, F-LBG算法, 声码器

Abstract: In order to overcome the defect of unnaturalness caused by hard decisions of voiced/unvoiced speech segments in LPC based low bit rate vocoder, a 5-dimensional voiced membership vector for accurately describing the information of excitation is proposed on the basis of analyzing and comparing the algorithms which are used by today’s mainstream vocoders for extracting and quantifying parameters of the excitation signal.  This paper introduces the concept of membership from fuzzy mathematics, describes the extracting algorithm of voiced membership vector and the VQ codebook of fuzzy clustering, and the LBG cascade training. Computer simulation experiments are conducted. The results indicate that this algorithm, using voiced membership vector to describe and synthesize the excitation signal, can achieve a very high accuracy and strong noise robustness when it is used to simulate the speech coding and decoding process for sinusoidal excitation vocoder, mixed-excitation vocoder and the homomorphic vocoder.

Key words: voiced membership, fuzzy clustering, Vector Quantization（VQ）, F-LBG algorithm, vocoder