• Publications
  • Influence
Computational auditory scene analysis
TLDR
We present a sound source segregation system that is consistent with psychological and physiological findings and is able to segregate speech from a variety of intrusive sounds, including other speech, with some success. Expand
  • 815
  • 47
Separation of speech from interfering sounds based on oscillatory correlation
  • D. Wang, G. Brown
  • Computer Science, Medicine
  • IEEE Trans. Neural Networks
  • 1 May 1999
TLDR
A multistage neural model is proposed for an auditory scene analysis task that performs stream segregation on the basis of oscillatory correlation. Expand
  • 321
  • 36
  • PDF
A multipitch tracking algorithm for noisy speech
TLDR
We present a robust algorithm for multipitch tracking of noisy speech that can reliably track single and double pitch tracks in noisy environment. Expand
  • 294
  • 36
Speech segregation based on sound localization
TLDR
We study the cocktail-party effect, which refers to the ability of a listener to attend to a single talker in the presence of adverse acoustical conditions. Expand
  • 352
  • 33
  • PDF
Computational auditory scene analysis : a representational approach
This thesis addresses the problem of how a listener groups together acoustic components which have arisen from the same environmental event, a phenomenon known as auditory scene analysis. AExpand
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A MATLAB Simulation of “ Shoebox ” Room Acoustics for use in Research and Teaching
A simulation of the acoustics of a simple rectangular prism room has been constructed using the MATLAB m-code programming language. The aim of this program (Roomsim) is to provide a signal generationExpand
  • 104
  • 13
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A binaural processor for missing data speech recognition in the presence of noise and small-room reverberation
TLDR
In this study we describe a binaural auditory model for recognition of speech in the presence of spatially separated noise intrusions, under small-room reverberation conditions. Expand
  • 123
  • 11
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Speech and crosstalk detection in multichannel audio
TLDR
A multichannel activity classification system has been described which can distinguish between the four activity categories shown in Table I. Tests performed on a large corpus of recorded meetings show classification accuracies of up to 96%. Expand
  • 121
  • 10
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Mask estimation for missing data speech recognition based on statistics of binaural interaction
TLDR
This paper describes a perceptually motivated computational auditory scene analysis (CASA) system that combines sound separation according to spatial location with the "missing data" approach for robust speech recognition in noise. Expand
  • 79
  • 9
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A computer model of auditory efferent suppression: implications for the recognition of speech in noise.
TLDR
The neural mechanisms underlying the ability of human listeners to recognize speech in the presence of background noise are still imperfectly understood. Expand
  • 59
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