상세정보
학술대회
Multi-level Stereo Attention Model for Center Channel Extraction
- 발행일
- 201906
- 출처
- International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB) 2019, pp.1-4
- 협약과제
- 18HS1700, 다중소스 데이터 지능형 분석기반 고수준 정보추출 원천기술 연구, 유장희
- 초록
- 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 제안 키워드
- 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