Predictive trellis-coded quantization of the cepstral coefficients for the distributed speech recognition

被引：0

作者：

Kang, Sangwon ^{[1
]}

Lee, Joonseok ^{[1
]}

机构：

[1] Hanyang Univ, Sch EECS, Ansan 426791, South Korea

来源：

IEICE TRANSACTIONS ON COMMUNICATIONS | 2007年 / E90B卷 / 06期

关键词：

distributed speech recognition (DER); cepstral coefficients; quantization; BC-TCQ;

D O I：

10.1093/ietcom/e90-b.6.1570

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this paper, we propose a predictive block-constrained trellis-coded quantization (BC-TCQ) to quantize cepstral coefficients for distributed speech recognition. For prediction of the cepstral coefficients, the first order auto-regressive (AR) predictor is used. To quantize the prediction error signal effectively, we use the BC-TCQ. The quantization is compared to the split vector quantizers used in the ETSI standard, and is shown to lower cepstral distance and bit rates.

引用

页码：1570 / 1572

页数：3

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