Speech presence detection in the time-frequency domain using minimum statistics
(2004) 6th Nordic Signal Processing Symposium (NORSIG 2004) 46. p.340-343- Abstract
- The contribution of this paper is a time-frequency domain speech presence detection method that classifies power bins in the time-frequency domain as containing speech or not. An initial decision rule is based on ratios between optimally time-smoothed signal-plus-noise periodograms and weighted noise periodogram estimates, obtained from minimum statistics as proposed by Martin [1]. The initial decision rule is generalized into a weighted decomposition where the weights are obtained from off-line training by, means of an artificial neural network. Experiments show that the method can be configured to be very sensitive to speech presence even in very high levels of noise and without classifying much of the noise as speech. It is shown that a... (More)
- The contribution of this paper is a time-frequency domain speech presence detection method that classifies power bins in the time-frequency domain as containing speech or not. An initial decision rule is based on ratios between optimally time-smoothed signal-plus-noise periodograms and weighted noise periodogram estimates, obtained from minimum statistics as proposed by Martin [1]. The initial decision rule is generalized into a weighted decomposition where the weights are obtained from off-line training by, means of an artificial neural network. Experiments show that the method can be configured to be very sensitive to speech presence even in very high levels of noise and without classifying much of the noise as speech. It is shown that a fixed set of weights gives good performance at different signal-to-noise ratios indicating that the terms in the decision rule have been adequately chosen. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4092548
- author
- Sorensen, KV and Andersen, Sören Vang LU
- publishing date
- 2004
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- NORSIG 2004: PROCEEDINGS OF THE 6TH NORDIC SIGNAL PROCESSING SYMPOSIUM
- volume
- 46
- pages
- 340 - 343
- publisher
- HELSINKI UNIVERSITY TECHNOLOGY
- conference name
- 6th Nordic Signal Processing Symposium (NORSIG 2004)
- conference dates
- 2004-06-09 - 2004-06-11
- external identifiers
-
- wos:000225463400086
- scopus:11844291956
- ISSN
- 1458-6401
- language
- English
- LU publication?
- no
- id
- f7ae5ed4-9bcf-4ccb-8f46-dbc9d66e6579 (old id 4092548)
- date added to LUP
- 2016-04-01 17:10:51
- date last changed
- 2022-01-29 00:55:29
@inproceedings{f7ae5ed4-9bcf-4ccb-8f46-dbc9d66e6579,
abstract = {{The contribution of this paper is a time-frequency domain speech presence detection method that classifies power bins in the time-frequency domain as containing speech or not. An initial decision rule is based on ratios between optimally time-smoothed signal-plus-noise periodograms and weighted noise periodogram estimates, obtained from minimum statistics as proposed by Martin [1]. The initial decision rule is generalized into a weighted decomposition where the weights are obtained from off-line training by, means of an artificial neural network. Experiments show that the method can be configured to be very sensitive to speech presence even in very high levels of noise and without classifying much of the noise as speech. It is shown that a fixed set of weights gives good performance at different signal-to-noise ratios indicating that the terms in the decision rule have been adequately chosen.}},
author = {{Sorensen, KV and Andersen, Sören Vang}},
booktitle = {{NORSIG 2004: PROCEEDINGS OF THE 6TH NORDIC SIGNAL PROCESSING SYMPOSIUM}},
issn = {{1458-6401}},
language = {{eng}},
pages = {{340--343}},
publisher = {{HELSINKI UNIVERSITY TECHNOLOGY}},
title = {{Speech presence detection in the time-frequency domain using minimum statistics}},
volume = {{46}},
year = {{2004}},
}