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Communication Dans Un Congrès Année : 2014

Online NON-negative Tensor Deconvolution for source detection in 3DTV audio

Résumé

The following article describes research on source detection in multi channel (3DTV) audio streams. The problem is extremely complex due to the fact that multiple layers can be present in scenes (background music, ambience, commentator). In this work a new algorithm is developed that exploits the information from the different audio channels to detect, and possibly localize and separate independent audio sources. An algorithm based on online Non-negative Tensor Deconvolution is realized, to deal with sound sources with time dependent positions in the channel matrix. The evaluation is made on 3DTV 5.1 film soundtracks and on synthetic mixes of 3DTV 5.1 audio with target sounds from a sound effects database: a significant improvement of the detection performance is shown, compared with other decomposition techniques.
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Dates et versions

hal-01107156 , version 1 (20-01-2015)

Identifiants

  • HAL Id : hal-01107156 , version 1

Citer

Yuki Mitsufuji, Marco Liuni, Alex R. Baker, Axel Roebel. Online NON-negative Tensor Deconvolution for source detection in 3DTV audio. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2014, Florence, Italie. pp.3082-3086. ⟨hal-01107156⟩
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