EURASIP Journal on Advances in Signal Processing - Special issue on microphone array speech processing
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
The 2010 signal separation evaluation campaign (SiSEC2010): audio source separation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
Adaptive fuzzy filter for speech enhancement
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part III
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Multi-modal sensing and analysis of poster conversations toward smart posterboard
SIGDIAL '12 Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Digital Signal Processing
Blind source extraction for robust speech recognition in multisource noisy environments
Computer Speech and Language
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Computer Speech and Language
Computer Speech and Language
Collaboration with a robotic scrub nurse
Communications of the ACM
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We propose a new blind spatial subtraction array (BSSA) consisting of a noise estimator based on independent component analysis (ICA) for efficient speech enhancement. In this paper, first, we theoretically and experimentally point out that ICA is proficient in noise estimation under a non-point-source noise condition rather than in speech estimation. Therefore, we propose BSSA that utilizes ICA as a noise estimator. In BSSA, speech extraction is achieved by subtracting the power spectrum of noise signals estimated using ICA from the power spectrum of the partly enhanced target speech signal with a delay-and-sum beamformer. This ldquopower-spectrum-domain subtractionrdquo procedure enables better noise reduction than the conventional ICA with estimation-error robustness. Another benefit of BSSA architecture is ldquopermutation robustness". Although the ICA part in BSSA suffers from a source permutation problem, the BSSA architecture can reduce the negative affection when permutation arises. The results of various speech enhancement test reveal that the noise reduction and speech recognition performance of the proposed BSSA are superior to those of conventional methods.