Tech report on speech segregation

[DeLiang Wang]

The following technical report is available via FTP/WWW:

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"Separation of Speech from Interfering Sounds 
Based on Oscillatory Correlation"

Technical Report #24, June 1998
The Ohio State University Center for Cognitive Science
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	DeLiang L. Wang, The Ohio State University
	Guy J. Brown, University of Sheffield

A multi-stage 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. Furthermore, the 
pattern of improvements seems consistent with human performance. The 
performance of our model is compared with other studies on computational 
auditory scene analysis. A number of issues including biological plausibility 
and real-time implementation are also discussed.

(28 pages, 384 KB compressed) 


for anonymous ftp:
       	FTP-HOST: ftp.cis.ohio-state.edu
	Directory: /pub/leon/Brown
       	Filename: ccs98.ps.gz

for WWW:
	http://www.cis.ohio-state.edu/~dwang/reports.html

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Send comments to DeLiang Wang (dwang at cis.ohio-state.edu)