Linear prediction based comfort noise generation in the EVS codec
Zhe Wang, Lei Miao, Jon Gibbs, Tomas Toftgard, Martin Sehlstedt, Stefan Bruhn, Venkatraman Atti, Vivek Rajendran
Abstract
A Discontinuous transmission (DTX) system, which is widely adopted in speech codecs, is an important function for speech communication systems that can reduce the transmission bandwidth by at least a half. Within a DTX system, the comfort noise generation (CNG) plays a key role in the overall quality. Critical performance parameters with respect to the CNG including the transition quality from active to comfort noise (CN) frame, the quality of CN spectrum estimation, wider bandwidth rendering and the DTX efficiency have all been found to be very important. This paper describes a series of new technologies developed for the EVS codec aiming to address the performance of the CNG: A new hangover based CN analysis technique provides improved CNG transition quality. A new entropy based CN spectrum estimation technique and a new hybrid CNG scheme improve the CN spectrum estimation. Finally, a novel bandwidth extension technique for efficient rendering of high-frequency CN and a novel technique improving the DTX efficiency by controlling the DTX hangover length are described.
BibTeX
@inproceedings{icassp2015_linearprediction,
title = {Linear prediction based comfort noise generation in the EVS codec},
author = {Zhe Wang and Lei Miao and Jon Gibbs and Tomas Toftgard and Martin Sehlstedt and Stefan Bruhn and Venkatraman Atti and Vivek Rajendran and Duminda A. Dewasurendra},
booktitle = {ICASSP 2015},
year = {2015}
}