Gradient-descent based window optimization for linear prediction analysis

被引：0
|
作者：
Chu, WC [1 ]
机构：
[1] DoCoMo USA Labs, Mobile Media Lab, San Jose, CA 95110 USA
来源：
2003 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL I, PROCEEDINGS: SPEECH PROCESSING I | 2003年
关键词：
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
The autocorrelation method of linear prediction (LP) analysis relies on a window for data extraction; we propose an approach to optimize the window based on gradient-descent. It is shown that the optimized window has improved performance with respect to popular windows, such as Hamming. The technique has potential in quality improvement for many LP-based speech coders.
引用
收藏
页码：460 / 463
页数：4
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