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低速语音编码中的预测分类分裂矢量量化技术*
引用本文:马庆利,季新生,杨于村.低速语音编码中的预测分类分裂矢量量化技术*[J].计算机应用研究,2009,26(10):3700-3702.
作者姓名:马庆利  季新生  杨于村
作者单位:1. 国家数字交换系统工程技术研究中心,郑州,450002
2. 华南理工大学,电信学院,广州,510641
基金项目:国家“863”计划资助项目(2007AA012431)
摘    要:为降低编码速率的同时仍能提供较好的谱失真性能,提出了一种预测分类分裂矢量量化算法,它根据线谱对的特点,融合了预测、分类、分裂的方法对线谱对进行量化,加入了记忆性。实验证明与其他几种方法相比,该算法的量化性能在速率与失真间达到了较好的平衡,且计算量大大降低,仅占有内存有所增加。

关 键 词:语音编码  线谱对  多级矢量量化  预测分类分裂矢量量化  谱失真

Predictive switched split vector quantiser of very low bit-rate speech coder
MA Qing-li,JI Xin-sheng,YANG Yu-cun.Predictive switched split vector quantiser of very low bit-rate speech coder[J].Application Research of Computers,2009,26(10):3700-3702.
Authors:MA Qing-li  JI Xin-sheng  YANG Yu-cun
Affiliation:(1.National Digital Switching System Engineering & Technological Research Center, Zhengzhou 450002, China;2.School of Electronic & Information Engineering, South China University of Technology, Guangzhou 510641, China)
Abstract:In order to reduce bit-rate and still maintain fine distortion performance, this paper proposed predictive switched split vector quantization method. It added memory according the characteristic of the LSP.And it was a hybrid of switched split vector quantization techniques. Experimental results show that the PSSVQ provides a better trade-off between bit-rate and distortion performance than the others. In addition, the PSSVQ has a lower computational (search) complexity at the expense of an increase in memory requirements.
Keywords:speech coding  line spectral pair(LSP)  multi-stage vector quantization(MSVQ)  predictive switched split vector quantization  spectral distortion
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