Tracking and data association
Pitch extraction and separation of overlapping speech
Speech Communication - Eurospeech '91
An extension of the Munkres algorithm for the assignment problem to rectangular matrices
Communications of the ACM
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
Statistical Models in S
A theory and computational model of auditory monaural sound separation (stream, speech enhancement, selective attention, pitch perception, noise cancellation)
Prediction-driven computational auditory scene analysis
Prediction-driven computational auditory scene analysis
Sound source separation via computational auditory scene analysis (casa)-enhanced beamforming
Sound source separation via computational auditory scene analysis (casa)-enhanced beamforming
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Separation of speech from interfering sounds based on oscillatory correlation
IEEE Transactions on Neural Networks
Monaural speech segregation based on pitch tracking and amplitude modulation
IEEE Transactions on Neural Networks
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Hearing aid users have difficulty hearing target signals, such as speech, in the presence of competing signals or noise. Most solutions proposed to date enhance or extract target signals from background noise and interference based on either location attributes or source attributes. Location attributes typically involve arrival angles at a microphone array. Source attributes include characteristics that are specific to a signal, such as fundamental frequency, or statistical properties that differentiate signals. This paper describes a novel approach to sound source separation, called computational auditory scene analysis-enhanced beamforming (CASA-EB), that achieves increased separation performance by combining the complementary techniques of CASA (a source attribute technique) with beamforming (a location attribute technique), complementary in the sense that they use independent attributes for signal separation. CASA-EB performs sound source separation by temporally and spatially filtering a multichannel input signal, and then grouping the resulting signal components into separated signals, based on source and location attributes. Experimental results show increased signal-to-interference ratio with CASA-EB over beamforming or CASA alone.