A Pruned-CELP Speech Codec Using Denoising Autoencoder with Spectral Compensation for Quality and Intelligibility Enhancement
Yu-Ting Lo, Syu‐Siang Wang, Yu Tsao, Sheng-Yu Peng · 2019
A codec based on the excited linear prediction (CELP) speech compression method adopting a denoising autoencoder with spectral compensation (DAE-SC) for quality and intelligibility enhancement is proposed in this paper. The sizes of CELP parameters in the encoder are carefully pruned to achieve a higher compression rate. To recover the speech quality and intelligibility degradation due to the pruned CELP parameters, a DAE-SC network with three hidden layers is employed in the decoder. Compared with the conventional CELP codec at a 9.6k bps transmission rate, the proposed speech codec achieves extra 21.9% bit rate reduction with comparable speech quality and intelligibility that are evaluated by four commonly used speech performance metrics.