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Journal Article Enhancement of Coded Speech Using Neural Network-Based Side Information
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Authors
Soojoong Hwang, Youngju Cheon, Sangwook Han, Inseon Jang, Jong Won Shin
Issue Date
2021-09
Citation
IEEE Access, v.9, pp.121532-121540
ISSN
2169-3536
Publisher
IEEE
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1109/ACCESS.2021.3108784
Abstract
Audio codecs generate notable artifacts when operating at low bitrates, which degrade the quality of the coded audio significantly. There have been several approaches to enhance the quality of decoded signals with and without side information. While pre- or post-processing approaches without side information can be applied directly to existing systems without modifying codecs, approaches utilizing side information can further enhance the performance while maintaining backward-compatibility with existing codecs. In this paper, we propose a method to improve decoded signals using neural network-based side information. A neural network in the transmitter side that generates the side information and another neural network in the receiver side that estimates the log power spectra (LPS) of the original signal from the decoded signal and the side information are jointly trained to accurately reconstruct the original signal. In the same line with the analysis-by-synthesis, the neural network that generates the side information in the transmitter side takes not only the LPS of the original signal but also the LPS of the decoded signal as the input by decoding the encoded bitstream at the transmitter side. Experimental results show that the proposed audio codec enhancement scheme using neural network-based side information outperformed the audio codec enhancement without side information for the same codec operating at higher bitrates.
KSP Keywords
Analysis-by-synthesis, Audio codec, Enhancement scheme, Network-based, Post-Processing, low bit rate, neural network(NN), power spectra, side information
This work is distributed under the term of Creative Commons License (CCL)
(CC BY NC ND)
CC BY NC ND