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Conference Paper Spatial-Cue Based Audio Channel Extension Using Convolutional Neural Networks
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Authors
Seungkwon Beack, Wootaek Lim, Taejin Lee
Issue Date
2019-06
Citation
International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) 2019, pp.1-4
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/BMSB47279.2019.8971936
Project Code
18HS1700, Basic Technology for Extracting High-level Information from Multiple Sources Data base on Intelligent Analysis, Yoo Jang-Hee
Abstract
In this paper, we introduce an audio channel extension tool using a spatial audio cue predicted using convolutional neural networks. The channel extension tool is applied into a common stereo signal to produce a high-dimensional audio signal, such as a 5.1 layout. To extend the channels from a stereo signal, we predict the spatial cues from the stereo signal, and synthesize the multichannel signals by allocating the spectral components according to the direction of the predicted spatial cues. Our subjective evaluation shows that a synthesized multichannel signal guarantees a high quality when compared with the original stereo signal.
KSP Keywords
Audio signal, Convolution neural network(CNN), High-dimensional, Multichannel signals, Spatial audio, Spatial cue, spectral components, subjective evaluation