ADAPTIVE SPEECH CODING WITH DCT AND NEURAL-NET VECTOR QUANTIZATION

被引：2

作者：

VELEVA, LV

KUNCHEV, RK

机构：

[1] Dept, of Radiocommunications and Signal Processing, Technical Univ. of Sofia

来源：

ELECTRONICS LETTERS | 1993年 / 29卷 / 08期

关键词：

SIGNAL PROCESSING; SPEECH PROCESSING; NEURAL NETWORKS; TRANSFORMS;

D O I：

10.1049/el:19930471

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：

A hybrid method for speech coding is presented based on the discrete cosine tranform (DCT) and neural net vector quantisation (NNVQ). The neural networks are trained off-line using a two stage learning algorithm. During the encoding process, neural net adaptation is carried out. Simulation results show a high compression factor and SNR.

引用

页码：704 / 705

页数：2

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