An Auditory Model-Inspired Objective Speech Intelligibility Estimate for Audio Systems
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J. Datta, X. Zhou, J. Begin, and M. Martin, "An Auditory Model-Inspired Objective Speech Intelligibility Estimate for Audio Systems," Paper 9918, (2018 May.). doi:
J. Datta, X. Zhou, J. Begin, and M. Martin, "An Auditory Model-Inspired Objective Speech Intelligibility Estimate for Audio Systems," Paper 9918, (2018 May.). doi:
Abstract: Compared with subjective tests, objective measures save time and money. This paper presents the implementation of a new algorithm for objective speech intelligibility, based on the modified rhyme test using real speech. An auditory-model inspired signal processing framework approach gathers word selection evidence in auditory filter bank correlations and then uses an auditory attention model to perform word selection. It has been shown to outperform popular measures in terms of Pearson correlation coefficient to the human intelligibility scores. A real-time version of this approach has been integrated into a versatile audio test and measurement system supporting a number of interfaces (different combinations of devices/channels/systems). Examples and measurement results will be presented to show the advantages of this approach.
@article{datta2018an,
author={datta, jayant and zhou, xinhui and begin, joe and martin, mark},
journal={journal of the audio engineering society},
title={an auditory model-inspired objective speech intelligibility estimate for audio systems},
year={2018},
volume={},
number={},
pages={},
doi={},
month={may},}
@article{datta2018an,
author={datta, jayant and zhou, xinhui and begin, joe and martin, mark},
journal={journal of the audio engineering society},
title={an auditory model-inspired objective speech intelligibility estimate for audio systems},
year={2018},
volume={},
number={},
pages={},
doi={},
month={may},
abstract={compared with subjective tests, objective measures save time and money. this paper presents the implementation of a new algorithm for objective speech intelligibility, based on the modified rhyme test using real speech. an auditory-model inspired signal processing framework approach gathers word selection evidence in auditory filter bank correlations and then uses an auditory attention model to perform word selection. it has been shown to outperform popular measures in terms of pearson correlation coefficient to the human intelligibility scores. a real-time version of this approach has been integrated into a versatile audio test and measurement system supporting a number of interfaces (different combinations of devices/channels/systems). examples and measurement results will be presented to show the advantages of this approach.},}
TY - paper
TI - An Auditory Model-Inspired Objective Speech Intelligibility Estimate for Audio Systems
SP -
EP -
AU - Datta, Jayant
AU - Zhou, Xinhui
AU - Begin, Joe
AU - Martin, Mark
PY - 2018
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2018
TY - paper
TI - An Auditory Model-Inspired Objective Speech Intelligibility Estimate for Audio Systems
SP -
EP -
AU - Datta, Jayant
AU - Zhou, Xinhui
AU - Begin, Joe
AU - Martin, Mark
PY - 2018
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - May 2018
AB - Compared with subjective tests, objective measures save time and money. This paper presents the implementation of a new algorithm for objective speech intelligibility, based on the modified rhyme test using real speech. An auditory-model inspired signal processing framework approach gathers word selection evidence in auditory filter bank correlations and then uses an auditory attention model to perform word selection. It has been shown to outperform popular measures in terms of Pearson correlation coefficient to the human intelligibility scores. A real-time version of this approach has been integrated into a versatile audio test and measurement system supporting a number of interfaces (different combinations of devices/channels/systems). Examples and measurement results will be presented to show the advantages of this approach.
Compared with subjective tests, objective measures save time and money. This paper presents the implementation of a new algorithm for objective speech intelligibility, based on the modified rhyme test using real speech. An auditory-model inspired signal processing framework approach gathers word selection evidence in auditory filter bank correlations and then uses an auditory attention model to perform word selection. It has been shown to outperform popular measures in terms of Pearson correlation coefficient to the human intelligibility scores. A real-time version of this approach has been integrated into a versatile audio test and measurement system supporting a number of interfaces (different combinations of devices/channels/systems). Examples and measurement results will be presented to show the advantages of this approach.
Authors:
Datta, Jayant; Zhou, Xinhui; Begin, Joe; Martin, Mark
Affiliation:
Audio Precision, Beaverton, OR, USA
AES Convention:
144 (May 2018)
Paper Number:
9918
Publication Date:
May 14, 2018Import into BibTeX
Subject:
Audio Quality Part 1
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=19435