A study on the reduction of LSP (line spectrum pair) computation using adjustment of search band sequence and interval

Soyeon Min, K. Jang, Myungjin Bae
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引用次数: 1

Abstract

We develop a computation reduction method for the real root method that is mainly used in the CELP (code excited linear prediction) vocoder. The real root method is that if polynomial equations have real roots, we are able to find those and transform them into LSP (line spectrum pairs). However, this method takes much time to compute, because the root searching is processed sequentially in the frequency region. But the important characteristic of LSP is that most coefficients occur in a specific frequency region. We suggest a method for reducing the LSP transformation time using voice characteristics. In the case of the silence period, the distribution of LSP parameters is uniform. In the case of the voice activity period, distribution of LSP parameters is not sequential. The proposed method applies search order and interval differently according to the distribution of LSP parameters. Also in the case of vowels, the search band can be controlled by the relation between the first formant and the second formant. When we compare this proposed method with the conventional real root method, the experimental result is that the searching time was reduced about 46% on average.
利用调整搜索频带序列和间隔减少LSP(线谱对)计算量的研究
本文提出了一种主要用于CELP(码激励线性预测)声码器的实根法的计算缩减方法。实根法是指如果多项式方程有实根,我们就可以找到这些实根,并将它们转化为LSP (line spectrum pairs)。但是,由于根搜索是在频率区域内顺序进行的,因此计算时间较长。但LSP的重要特点是大多数系数都出现在特定的频率区域。我们提出了一种利用语音特征减少LSP转换时间的方法。在静默时间的情况下,LSP参数的分布是均匀的。在语音活动周期的情况下,LSP参数的分布不是顺序的。该方法根据LSP参数的分布情况,采用不同的搜索顺序和间隔。在元音的情况下,搜索频带也可以通过第一共振峰和第二共振峰之间的关系来控制。实验结果表明,与传统的实数根方法相比,该方法的搜索时间平均缩短了46%左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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