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

H. Relaño-Iborra; Tobias May; Johannes Zaar; Christoph Scheidiger; Torsten Dau

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

H. Relaño-Iborra, Tobias May, Johannes Zaar, Christoph Scheidiger, Torsten Dau

Research output: Contribution to conference › Poster › Research › peer-review

297 Downloads (Orbit)

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 language	English
Publication date	2016
Publication status	Published - 2016
Event	ARCHES/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 2016 → 23 Nov 2016 http://www.uzh.ch/orl/events/Arches2016/Program2016/program2016.html

Conference

Conference	ARCHES/ICANHEAR 2016
Location	University of Zurich
Country/Territory	Switzerland
City	Zurich
Period	21/11/2016 → 23/11/2016
Internet address	http://www.uzh.ch/orl/events/Arches2016/Program2016/program2016.html

Access to Document

ARCHES poster final3Final published version, 531 KB

OpenUrl availability

Full text

A correlation metric in the envelope power spectrum domain for speech intelligibility prediction
Iborra, H. R. (Guest lecturer)
2017
Activity: Talks and presentations › Conference presentations

File

Cite this

@conference{c13a42ca4f004be2a0ec1471b3929377,

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",

}

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

T2 - ARCHES/ICANHEAR 2016

Y2 - 21 November 2016 through 23 November 2016

ER -

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

Abstract

Conference

Access to Document

OpenUrl availability

Fingerprint

Activities

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

Cite this