Computational auditory scene analysis
Computational auditory scene analysis
The Journal of Machine Learning Research
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications
Geometrical interpretation of the PCA subspace approach for overdetermined blind source separation
EURASIP Journal on Applied Signal Processing
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Model-based expectation-maximization source separation and localization
IEEE Transactions on Audio, Speech, and Language Processing
Infinite sparse factor analysis and infinite independent components analysis
ICA'07 Proceedings of the 7th international conference on Independent component analysis and signal separation
Handbook of Blind Source Separation: Independent Component Analysis and Applications
Handbook of Blind Source Separation: Independent Component Analysis and Applications
Under-determined reverberant audio source separation using a full-rank spatial covariance model
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on processing reverberant speech: methodologies and applications
Complex extension of infinite sparse factor analysis for blind speech separation
LVA/ICA'12 Proceedings of the 10th international conference on Latent Variable Analysis and Signal Separation
Blind separation of speech mixtures via time-frequency masking
IEEE Transactions on Signal Processing
Performance measurement in blind audio source separation
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
Blind Separation and Dereverberation of Speech Mixtures by Joint Optimization
IEEE Transactions on Audio, Speech, and Language Processing
The multivariate complex normal distribution-a generalization
IEEE Transactions on Information Theory
Hi-index | 0.00 |
Sound source localization and separation from a mixture of sounds are essential functions for computational auditory scene analysis. The main challenges are designing a unified framework for joint optimization and estimating the sound sources under auditory uncertainties such as reverberation or unknown number of sounds. Since sound source localization and separation are mutually dependent, their simultaneous estimation is required for better and more robust performance. A unified model is presented for sound source localization and separation based on Bayesian nonparametrics. Experiments using simulated and recorded audio mixtures show that a method based on this model achieves state-of-the-art sound source separation quality and has more robust performance on the source number estimation under reverberant environments.