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Conference Paper
Multi-level Stereo Attention Model for Center Channel Extraction
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- Authors
- Wootaek Lim, Seungkwon Beack, Taejin Lee
- Issue Date
- 2019-06
- Citation
- International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) 2019, pp.1-4
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- In recent years, the spatial audio reproduction of digital media has become popular. Despite the demand for such spatial audio content, very little content is produced with multi-channel audio. Moreover, it is difficult to provide interactive services to users owing to the lack of object-based content. In this paper, we propose a center channel extraction method based on a multi-level convolutional neural network structure to generate object-based content. In addition, we present a novel stereo attention model which considers each channel's characteristics. By applying the proposed method to stereo audio content, we achieve better extraction performance than existing commercial application.
- KSP Keywords
- Attention model, Commercial application, Convolution neural network(CNN), Digital Media, Extraction method, Interactive services, Multi-level, Multichannel audio, Neural network structure, Object-based, S characteristics