Logistic discriminative speech detectors using posterior SNR

We introduce an elegant and novel design for a speech detector which estimates the probability of the presence of speech in each time-frequency bin, as well as in each frame. The proposed system uses discriminative estimators based on logistic regression, and incorporates spectral and temporal corre...

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Bibliographic Details
Main Authors: Surendran, A.C., Sukittanon, S., Platt, J.
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Detectors
Exact sciences and technology
Information, signal and communications theory
Logistics
Noise generators
Signal design
Signal processing
Signal to noise ratio
Spatial databases
Speech coding
Speech enhancement
Speech processing
Telecommunications and information theory
Testing
Time frequency analysis
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Description
Summary:We introduce an elegant and novel design for a speech detector which estimates the probability of the presence of speech in each time-frequency bin, as well as in each frame. The proposed system uses discriminative estimators based on logistic regression, and incorporates spectral and temporal correlations in the same framework. The detector is flexible enough to be configured in a single level or a "stacked" bilevel architecture depending on the needs of the application. An important part of the proposed design is the use of a new set of features: the normalized logarithm of the estimated posterior signal-to-noise ratio. These can be easily and automatically generated by tracking the noise spectrum online. We present results on the AURORA database to demonstrate that the overall design is simple, flexible and effective.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2004.1327188