A Neural Oscillator Model of Auditory Attention
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
A maximum likelihood approach to single-channel source separation
The Journal of Machine Learning Research
A maximum likelihood approach to single-channel source separation
The Journal of Machine Learning Research
Neural Computation
A Biologically Motivated Solution to the Cocktail Party Problem
Neural Computation
On noise masking for automatic missing data speech recognition: A survey and discussion
Computer Speech and Language
Source separation with one ear: proposition for an anthropomorphic approach
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Audio, Speech, and Music Processing
On the optimality of ideal binary time-frequency masks
Speech Communication
Monaural speech separation based on MAXVQ and CASA for robust speech recognition
Computer Speech and Language
A computational auditory scene analysis system for speech segregation and robust speech recognition
Computer Speech and Language
Robust speech recognition by integrating speech separation and hypothesis testing
Speech Communication
WCCI'08 Proceedings of the 2008 IEEE world conference on Computational intelligence: research frontiers
A computational auditory scene analysis-enhanced beamforming approach for sound source separation
EURASIP Journal on Advances in Signal Processing - Special issue on digital signal processing for hearing instruments
IEEE Transactions on Audio, Speech, and Language Processing
A tandem algorithm for pitch estimation and voiced speech segregation
IEEE Transactions on Audio, Speech, and Language Processing
Single-channel speech separation based on long-short frame associated harmonic model
Digital Signal Processing
Monaural voiced speech segregation based on dynamic harmonic function
EURASIP Journal on Audio, Speech, and Music Processing
Optical Memory and Neural Networks
BLUES from music: BLind underdetermined extraction of sources from music
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Separating underdetermined convolutive speech mixtures
ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
Perceptive, non-linear speech processing and spiking neural networks
Nonlinear Speech Modeling and Applications
Nonlinear Speech Modeling and Applications
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A multistage neural model is proposed for an auditory scene analysis task-segregating speech from interfering sound sources. The core of the model is a two-layer oscillator network that performs stream segregation on the basis of oscillatory correlation. In the oscillatory correlation framework, a stream is represented by a population of synchronized relaxation oscillators, each of which corresponds to an auditory feature, and different streams are represented by desynchronized oscillator populations. Lateral connections between oscillators encode harmonicity, and proximity in frequency and time. Prior to the oscillator network are a model of the auditory periphery and a stage in which mid-level auditory representations are formed. The model has been systematically evaluated using a corpus of voiced speech mixed with interfering sounds, and produces improvements in terms of signal-to-noise ratio for every mixture. A number of issues including biological plausibility and real-time implementation are also discussed