RNN-based signal classification for hybrid audio data compression-Reference-Cited by-同舟云学术

RNN-based signal classification for hybrid audio data compression

Published:2019-03-26 Issue:3 Volume:102 Page:813-827
ISSN:0010-485X
Container-title:Computing
language:en
Short-container-title:Computing

Author:

Tu Weiping^ORCID,Yang Yuhong,Du Bo,Yang Wanzhao,Zhang Xiong,Zheng Jiaxi

Funder

Technological Innovation Major Project of Hubei Province

National Nature Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Numerical Analysis,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s00607-019-00713-8.pdf

Reference28 articles.

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2. GPP (2014) Recommendation TS 26.441. Codec for enhanced voice services (EVS)

3. MPEG (2011) Recommendation ISO/IEC 23003-3, information technology–MPEG audio technologies—part 3: unified speech and audio coding

4. Jérémie L, Roch L, Guy R (2007) An improved low complexity AMR-WB+ encoder using neural networks for mode selection. In: 123rd convention of audio engineering society

5. Jong-Kyu K, Nam-Soo K (2008) Improved frame mode selection for AMR-WB+ based on decision tree. IEICE Trans INF Syst E 91-D(6):1830–1833

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