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• W2925717635 abstract "We propose a blind source separation algorithm that jointly exploits measurements by a conventional microphone array and an ad hoc array of low-rate sound power sensors called blinkies. While providing less information than microphones, blinkies circumvent some difficulties of microphone arrays in terms of manufacturing, synchronization, and deployment. The algorithm is derived from a joint probabilistic model of the microphone and sound power measurements. We assume the separated sources to follow a time-varying spherical Gaussian distribution, and the non-negative power measurement space-time matrix to have a low-rank structure. We show that alternating updates similar to those of independent vector analysis and Itakura-Saito non-negative matrix factorization decrease the negative log-likelihood of the joint distribution. The proposed algorithm is validated via numerical experiments. Its median separation performance is found to be up to 8 dB more than that of independent vector analysis, with significantly reduced variability." @default.
• W2925717635 created "2019-04-11" @default.
• W2925717635 creator A5020401831 @default.
• W2925717635 creator A5056281759 @default.
• W2925717635 date "2019-05-01" @default.
• W2925717635 modified "2023-10-14" @default.
• W2925717635 title "Multi-modal Blind Source Separation with Microphones and Blinkies" @default.
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• W2925717635 doi "https://doi.org/10.1109/icassp.2019.8682594" @default.
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