A correlation metric in the envelope power spectrum domain for speech intelligibility prediction

Research output: Contribution to conferencePosterResearchpeer-review

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Abstract

A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speech-based envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envelope Power Spectrum Model (mr-sEPSM) [2], combined with the correlation back-end of the Short-Time Objective Intelligibility measure (STOI) [3]. The sEPSMcorr can accurately predict NH data for a broad range of listening conditions, e.g., additive noise, phase jitter and ideal binary mask processing
Original languageEnglish
Publication date2016
Publication statusPublished - 2016
EventARCHES/ICANHEAR 2016: Audiological Research Cores in Europe (ARCHES) meeting and Improved Communication through Applied Hearing Research (ICanHear) conference - University of Zurich, Zurich, Switzerland
Duration: 21 Nov 201623 Nov 2016
http://www.uzh.ch/orl/events/Arches2016/Program2016/program2016.html

Conference

ConferenceARCHES/ICANHEAR 2016
LocationUniversity of Zurich
CountrySwitzerland
CityZurich
Period21/11/201623/11/2016
Internet address

Cite this

Relaño-Iborra, H., May, T., Zaar, J., Scheidiger, C., & Dau, T. (2016). A correlation metric in the envelope power spectrum domain for speech intelligibility prediction. Poster session presented at ARCHES/ICANHEAR 2016, Zurich, Switzerland.
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title = "A correlation metric in the envelope power spectrum domain for speech intelligibility prediction",
abstract = "A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speech-based envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envelope Power Spectrum Model (mr-sEPSM) [2], combined with the correlation back-end of the Short-Time Objective Intelligibility measure (STOI) [3]. The sEPSMcorr can accurately predict NH data for a broad range of listening conditions, e.g., additive noise, phase jitter and ideal binary mask processing",
author = "H. Rela{\~n}o-Iborra and Tobias May and Johannes Zaar and Christoph Scheidiger and Torsten Dau",
year = "2016",
language = "English",
note = "ARCHES/ICANHEAR 2016 : Audiological Research Cores in Europe (ARCHES) meeting and Improved Communication through Applied Hearing Research (ICanHear) conference, ARCHES/ICANHEAR ; Conference date: 21-11-2016 Through 23-11-2016",
url = "http://www.uzh.ch/orl/events/Arches2016/Program2016/program2016.html",

}

Relaño-Iborra, H, May, T, Zaar, J, Scheidiger, C & Dau, T 2016, 'A correlation metric in the envelope power spectrum domain for speech intelligibility prediction' ARCHES/ICANHEAR 2016, Zurich, Switzerland, 21/11/2016 - 23/11/2016, .

A correlation metric in the envelope power spectrum domain for speech intelligibility prediction. / Relaño-Iborra, H.; May, Tobias; Zaar, Johannes; Scheidiger, Christoph; Dau, Torsten.

2016. Poster session presented at ARCHES/ICANHEAR 2016, Zurich, Switzerland.

Research output: Contribution to conferencePosterResearchpeer-review

TY - CONF

T1 - A correlation metric in the envelope power spectrum domain for speech intelligibility prediction

AU - Relaño-Iborra, H.

AU - May, Tobias

AU - Zaar, Johannes

AU - Scheidiger, Christoph

AU - Dau, Torsten

PY - 2016

Y1 - 2016

N2 - A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speech-based envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envelope Power Spectrum Model (mr-sEPSM) [2], combined with the correlation back-end of the Short-Time Objective Intelligibility measure (STOI) [3]. The sEPSMcorr can accurately predict NH data for a broad range of listening conditions, e.g., additive noise, phase jitter and ideal binary mask processing

AB - A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speech-based envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envelope Power Spectrum Model (mr-sEPSM) [2], combined with the correlation back-end of the Short-Time Objective Intelligibility measure (STOI) [3]. The sEPSMcorr can accurately predict NH data for a broad range of listening conditions, e.g., additive noise, phase jitter and ideal binary mask processing

M3 - Poster

ER -

Relaño-Iborra H, May T, Zaar J, Scheidiger C, Dau T. A correlation metric in the envelope power spectrum domain for speech intelligibility prediction. 2016. Poster session presented at ARCHES/ICANHEAR 2016, Zurich, Switzerland.