量化(信号处理)
线性预测编码
算法
数学
语音编码
矢量量化
线性预测
语音识别
编码(社会科学)
码激励线性预测
缩小
计算机科学
数学优化
统计
作者
Frank K. Soong,B.-H. Juang
出处
期刊:IEEE Transactions on Speech and Audio Processing
[Institute of Electrical and Electronics Engineers]
日期:1993-01-01
卷期号:1 (1): 15-24
被引量:155
摘要
Two nonuniform aspects of the line spectrum pair (LSP) linear predictive coding (LPC) parameters are investigated, including nonuniform statistical distributions and spectral sensitivities of adjacent LSP frequency differences. Based upon these two nonuniform properties, a globally optimal scalar quantizer is designed for each differential LSP frequency. The design algorithm is dynamic programming based and minimization of a nontrivial data dependent spectral distortion is adopted as the optimality criterion. At 32 bits/frame, the new LSP quantizer achieves a 1-dB average log spectral distortion, a commonly accepted level for reproducing perceptually transparent spectral information. The quantization performance has also been shown to be robust across different speakers and databases.< >
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