An Oscillatory Correlation Frame Work for Computational Auditory Scene Analysis
Abstract
A neural model is described which uses oscillatory correlation to segregate speech from interfering sound sources. The core of the model is a two-layer neural oscillator network. A sound stream is represented by a synchronized population of oscillators, and different streams are represented by desynchronized oscillator populations. The model has been evaluated using a corpus of speech mixed with interfering sounds, and produces an improvement in signal-to-noise ratio for every mixture.
Cite
Text
Brown and Wang. "An Oscillatory Correlation Frame Work for Computational Auditory Scene Analysis." Neural Information Processing Systems, 1999.Markdown
[Brown and Wang. "An Oscillatory Correlation Frame Work for Computational Auditory Scene Analysis." Neural Information Processing Systems, 1999.](https://mlanthology.org/neurips/1999/brown1999neurips-oscillatory/)BibTeX
@inproceedings{brown1999neurips-oscillatory,
title = {{An Oscillatory Correlation Frame Work for Computational Auditory Scene Analysis}},
author = {Brown, Guy J. and Wang, DeLiang L.},
booktitle = {Neural Information Processing Systems},
year = {1999},
pages = {747-753},
url = {https://mlanthology.org/neurips/1999/brown1999neurips-oscillatory/}
}