A Model to Predict the Impact of Dialog Enhancement or Mix Ratio on a Large Audience
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A. Master, and H. Muesch, "A Model to Predict the Impact of Dialog Enhancement or Mix Ratio on a Large Audience," Engineering Brief 637, (2020 October.). doi:
A. Master, and H. Muesch, "A Model to Predict the Impact of Dialog Enhancement or Mix Ratio on a Large Audience," Engineering Brief 637, (2020 October.). doi:
Abstract: Increasing the speech-to-background mix ratio of content, either algorithmically through dialog enhancement (DE), or during production, is considered a means of reducing listening effort for an audience, some members of which have hearing impairments. But what exactly is the expected benefit? A portion of the audience can already follow the content effortlessly and dialog boosting will not improve their perception. Other parts of the audience are severely impaired, and their speech reception performance will improve until all background is removed. We introduce a model that predicts which parts of an audience benefit by how much from changing the speech-to-background mix ratio of a piece of content. The model is intended to allow decision makers to predict what impact changes in audio production guidelines or DE technologies will have on their audience.
@article{master2020a,
author={master, aaron and muesch, hannes},
journal={journal of the audio engineering society},
title={a model to predict the impact of dialog enhancement or mix ratio on a large audience},
year={2020},
volume={},
number={},
pages={},
doi={},
month={october},}
@article{master2020a,
author={master, aaron and muesch, hannes},
journal={journal of the audio engineering society},
title={a model to predict the impact of dialog enhancement or mix ratio on a large audience},
year={2020},
volume={},
number={},
pages={},
doi={},
month={october},
abstract={increasing the speech-to-background mix ratio of content, either algorithmically through dialog enhancement (de), or during production, is considered a means of reducing listening effort for an audience, some members of which have hearing impairments. but what exactly is the expected benefit? a portion of the audience can already follow the content effortlessly and dialog boosting will not improve their perception. other parts of the audience are severely impaired, and their speech reception performance will improve until all background is removed. we introduce a model that predicts which parts of an audience benefit by how much from changing the speech-to-background mix ratio of a piece of content. the model is intended to allow decision makers to predict what impact changes in audio production guidelines or de technologies will have on their audience.},}
TY - paper
TI - A Model to Predict the Impact of Dialog Enhancement or Mix Ratio on a Large Audience
SP -
EP -
AU - Master, Aaron
AU - Muesch, Hannes
PY - 2020
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2020
TY - paper
TI - A Model to Predict the Impact of Dialog Enhancement or Mix Ratio on a Large Audience
SP -
EP -
AU - Master, Aaron
AU - Muesch, Hannes
PY - 2020
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2020
AB - Increasing the speech-to-background mix ratio of content, either algorithmically through dialog enhancement (DE), or during production, is considered a means of reducing listening effort for an audience, some members of which have hearing impairments. But what exactly is the expected benefit? A portion of the audience can already follow the content effortlessly and dialog boosting will not improve their perception. Other parts of the audience are severely impaired, and their speech reception performance will improve until all background is removed. We introduce a model that predicts which parts of an audience benefit by how much from changing the speech-to-background mix ratio of a piece of content. The model is intended to allow decision makers to predict what impact changes in audio production guidelines or DE technologies will have on their audience.
Increasing the speech-to-background mix ratio of content, either algorithmically through dialog enhancement (DE), or during production, is considered a means of reducing listening effort for an audience, some members of which have hearing impairments. But what exactly is the expected benefit? A portion of the audience can already follow the content effortlessly and dialog boosting will not improve their perception. Other parts of the audience are severely impaired, and their speech reception performance will improve until all background is removed. We introduce a model that predicts which parts of an audience benefit by how much from changing the speech-to-background mix ratio of a piece of content. The model is intended to allow decision makers to predict what impact changes in audio production guidelines or DE technologies will have on their audience.
Open Access
Authors:
Master, Aaron; Muesch, Hannes
Affiliation:
Dolby Laboratories, San Francisco, CA, USA
AES Convention:
149 (October 2020)eBrief:637
Publication Date:
October 22, 2020Import into BibTeX
Subject:
Perception
Permalink:
http://www.aes.org/e-lib/browse.cfm?elib=20923
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