scholarly journals Harp-Net: Hyper-Autoencoded Reconstruction Propagation for Scalable Neural Audio Coding

Author(s):  
Darius Petermann ◽  
Seungkwon Beack ◽  
Minje Kim
Keyword(s):  
1998 ◽  
Vol 6 (2) ◽  
pp. 186-189 ◽  
Author(s):  
F. Kossentini ◽  
M. Macon ◽  
M.J.T. Smith
Keyword(s):  

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Young Han Lee ◽  
Seung Ho Choi

A bandwidth extension (BWE) algorithm from wideband to superwideband (SWB) is proposed for a scalable speech/audio codec that uses modified discrete cosine transform (MDCT) coefficients as spectral parameters. The superwideband is first split into several subbands that are represented as gain parameters and normalized MDCT coefficients in the proposed BWE algorithm. We then estimate normalized MDCT coefficients of the wideband to be fetched for the superwideband and quantize the fetch indices. After that, we quantize gain parameters by using relative ratios between adjacent subbands. The proposed BWE algorithm is embedded into a standard superwideband codec, the SWB extension of G.729.1 Annex E, and its bitrate and quality are compared with those of the BWE algorithm already employed in the standard superwideband codec. It is shown from the comparison that the proposed BWE algorithm relatively reduces the bitrate by around 19% with better quality, compared to the BWE algorithm in the SWB extension of G.729.1 Annex E.


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