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
收藏
页码：704 / 705
页数：2
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