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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
- 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