Distortion Reduction via CAE and DenseNet Mixture Network for Low Bitrate Spatial Audio Object Coding

2022 ◽  
pp. 1-1
Author(s):  
Yulin Wu ◽  
Ruimin Hu ◽  
Xiaochen Wang ◽  
Chenhao Hu ◽  
Shanfa Ke
Author(s):  
Chenhao Hu ◽  
Ruimin Hu ◽  
Xiaochen Wang ◽  
Tingzhao Wu ◽  
Dengshi Li
Keyword(s):  

2011 ◽  
Vol 13 (6) ◽  
pp. 1208-1216 ◽  
Author(s):  
Kwangki Kim ◽  
Jeongil Seo ◽  
Seungkwon Beack ◽  
Kyeongok Kang ◽  
Minsoo Hahn
Keyword(s):  

2013 ◽  
Vol 2013 ◽  
pp. 1-21 ◽  
Author(s):  
Petr Motlicek ◽  
Stefan Duffner ◽  
Danil Korchagin ◽  
Hervé Bourlard ◽  
Carl Scheffler ◽  
...  

We describe the design of a system consisting of several state-of-the-art real-time audio and video processing components enabling multimodal stream manipulation (e.g., automatic online editing for multiparty videoconferencing applications) in open, unconstrained environments. The underlying algorithms are designed to allow multiple people to enter, interact, and leave the observable scene with no constraints. They comprise continuous localisation of audio objects and its application for spatial audio object coding, detection, and tracking of faces, estimation of head poses and visual focus of attention, detection and localisation of verbal and paralinguistic events, and the association and fusion of these different events. Combined all together, they represent multimodal streams with audio objects and semantic video objects and provide semantic information for stream manipulation systems (like a virtual director). Various experiments have been performed to evaluate the performance of the system. The obtained results demonstrate the effectiveness of the proposed design, the various algorithms, and the benefit of fusing different modalities in this scenario.


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