{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:10:13Z","timestamp":1792786213367,"version":"4.5.0"},"reference-count":46,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2018,3,1]],"date-time":"2018-03-01T00:00:00Z","timestamp":1519862400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"funder":[{"name":"Hearing4all","award":["1077\/1"],"award-info":[{"award-number":["1077\/1"]}],"id":[{"id":"https:\/\/ror.org\/0393vzh87","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Hearing Research"],"published-print":{"date-parts":[[2018,3]]},"DOI":"10.1016\/j.heares.2017.12.014","type":"journal-article","created":{"date-parts":[[2017,12,27]],"date-time":"2017-12-27T19:58:53Z","timestamp":1514404733000},"page":"40-49","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":19,"special_numbering":"C","title":["Single-ended prediction of listening effort using deep neural networks"],"prefix":"10.1016","volume":"359","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7241-2037","authenticated-orcid":false,"given":"Rainer","family":"Huber","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Melanie","family":"Kr\u00fcger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernd T.","family":"Meyer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.heares.2017.12.014_bib1","series-title":"ANSI S3.5\u20131997, American National Standard Methods for Calculation of the Speech Intelligibility Index","author":"ANSI","year":"1997"},{"key":"10.1016\/j.heares.2017.12.014_bib2","series-title":"Proceedings Conference of the IEEE Eng. Med. Biol. Soc. 2014","first-page":"2653","article-title":"Objective assessment of listening effort in the oscillatory EEG: comparison of different hearing aid configurations","author":"Bernarding","year":"2014"},{"key":"10.1016\/j.heares.2017.12.014_bib3","doi-asserted-by":"crossref","first-page":"1562","DOI":"10.1121\/1.2166600","article-title":"A\u00a0glimpsing model of speech perception in noise","volume":"119","author":"Cooke","year":"2006","journal-title":"J.\u00a0Acoust. Soc. Am."},{"key":"10.1016\/j.heares.2017.12.014_bib4","series-title":"Proceedings 8th International Conference on Signal Processing and Communication Systems (ICSPCS)","article-title":"Enhanced forensic multiple speaker recognition in the presence of coloured noise","author":"Denk","year":"2014"},{"issue":"3","key":"10.1016\/j.heares.2017.12.014_bib5","doi-asserted-by":"crossref","first-page":"148","DOI":"10.3109\/00206090109073110","article-title":"ICRA noises: artificial noise signals with speech-like spectral and temporal properties for hearing instrument assessment","volume":"40","author":"Dreschler","year":"2001","journal-title":"Int. J. Audiol."},{"issue":"6","key":"10.1016\/j.heares.2017.12.014_bib6","doi-asserted-by":"crossref","first-page":"1109","DOI":"10.1109\/TASSP.1984.1164453","article-title":"Speech enhancement using a minimum mean-square error short-time spectral amplitude estimator","volume":"32","author":"Ephraim","year":"1984","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"10.1016\/j.heares.2017.12.014_bib7","series-title":"CSR-I (WSJ0) Complete. Linguistic Data Consortium","author":"Garofalo","year":"2007"},{"key":"10.1016\/j.heares.2017.12.014_bib8","series-title":"DFT-Domain Based Single-microphone Noise Reduction for Speech Enhancement-a Survey of the State of the Art","author":"Hendriks","year":"2013"},{"key":"10.1016\/j.heares.2017.12.014_bib9","series-title":"Proceedings ICASSP 2013, 38th IEEE Int. Conf. Acoust. Speech Signal Process","article-title":"Mean temporal distance: predicting ASR error from temporal properties of speech signal","author":"Hermansky","year":"2013"},{"key":"10.1016\/j.heares.2017.12.014_bib10","doi-asserted-by":"crossref","DOI":"10.1109\/MSP.2012.2205597","article-title":"Deep neural networks for acoustic modeling in speech recognition","author":"Hinton","year":"2012","journal-title":"IEEE Signal Process. Mag."},{"key":"10.1016\/j.heares.2017.12.014_bib11","doi-asserted-by":"crossref","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","article-title":"A\u00a0fast learning algorithm for deep belief nets","volume":"18","author":"Hinton","year":"2006","journal-title":"Neural Comput."},{"key":"10.1016\/j.heares.2017.12.014_bib13","series-title":"Proceedings INTERSPEECH 2017-18th Annual Conference of the International Speech Communication Association, Stockholm, Sweden","article-title":"Single-ended prediction of listening effort based on automatic speech recognition","author":"Huber","year":"2017"},{"key":"10.1016\/j.heares.2017.12.014_bib14","series-title":"2nd Workshop on Speech in Noise: Intelligibility and Quality, Amsterdam, The Netherlands","article-title":"Objective measures of speech quality in hearing aids: prediction of listening effort reduction by noise reduction algorithms","author":"Huber","year":"2010"},{"issue":"6","key":"10.1016\/j.heares.2017.12.014_bib15","doi-asserted-by":"crossref","first-page":"1902","DOI":"10.1109\/TASL.2006.883259","article-title":"PEMO-Q - a new method for objective audio quality assessment using a model of auditory perception","volume":"14","author":"Huber","year":"2006","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"key":"10.1016\/j.heares.2017.12.014_bib16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/14992027.2017.1279758","article-title":"Comparison of single-microphone noise reduction schemes: can hearing impaired listeners tell the difference?","volume":"23","author":"Huber","year":"2017","journal-title":"Int. J. Audiol."},{"key":"10.1016\/j.heares.2017.12.014_bib17","series-title":"Single-ended Method for Objective Speech Quality Assessment in Narrow-band Telephony Applications","author":"ITU-T","year":"2004"},{"key":"10.1016\/j.heares.2017.12.014_bib18","series-title":"Methods for Objective and Subjective Assessment of Speech Quality (POLQA): Perceptual Objective Listening Quality Assessment","author":"ITU-T","year":"2014"},{"issue":"1","key":"10.1016\/j.heares.2017.12.014_bib19","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1002\/bltj.20228","article-title":"ANIQUE+: a new American national standard for non-intrusive estimation of narrowband speech quality","volume":"12","author":"Kim","year":"2007","journal-title":"Bell Labs Tech. J."},{"issue":"2","key":"10.1016\/j.heares.2017.12.014_bib20","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1097\/AUD.0b013e3182310019","article-title":"Pupil dilation uncovers extra listening effort in the presence of a single-talker masker","volume":"33","author":"Koelewijn","year":"2012","journal-title":"Ear Hear."},{"key":"10.1016\/j.heares.2017.12.014_bib21","doi-asserted-by":"crossref","first-page":"155","DOI":"10.3109\/00206099709071969","article-title":"Assessing aspects of auditory handicap by means of pupil dilatation","volume":"36","author":"Kramer","year":"1997","journal-title":"Audiology"},{"issue":"6","key":"10.1016\/j.heares.2017.12.014_bib22","doi-asserted-by":"crossref","first-page":"4680","DOI":"10.1121\/1.4986938","article-title":"Development of an adaptive scaling method for subjective listening effort","volume":"141","author":"Krueger","year":"2017","journal-title":"J.\u00a0Acoust. Soc. Am."},{"issue":"1","key":"10.1016\/j.heares.2017.12.014_bib23","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1097\/AUD.0000000000000091","article-title":"Effects of hearing loss on heart-rate variability and skin conductance measured during sentence recognition in noise","volume":"36","author":"Mackersie","year":"2015","journal-title":"Ear Hear."},{"key":"10.1016\/j.heares.2017.12.014_bib24","series-title":"Proceedings IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU","article-title":"Uncertainty estimation of DNN classifiers","author":"Mallidi","year":"2016"},{"issue":"1","key":"10.1016\/j.heares.2017.12.014_bib25","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1121\/1.3514525","article-title":"Effect of speech-intrinsic variations on human and automatic recognition of spoken phonemes","volume":"129","author":"Meyer","year":"2011","journal-title":"J.\u00a0Acoust. Soc. Am."},{"key":"10.1016\/j.heares.2017.12.014_bib26","series-title":"Proceedings INTERSPEECH 2010-11th Annual Conference of the International Speech Communication Association, Makuhari, Japan","article-title":"Learning from human errors: prediction of phoneme confusions based on modified ASR training","author":"Meyer","year":"2010"},{"key":"10.1016\/j.heares.2017.12.014_bib27","series-title":"Proceedings ICASSP 2017-42nd IEEE Int. Conf. Acoust. Speech Signal Process., March 5-9, New Orleans, USA","article-title":"Predicting error rates for unknown data in automatic speech recognition","author":"Meyer","year":"2017"},{"key":"10.1016\/j.heares.2017.12.014_bib28","article-title":"Performance monitoring for automatic speech recognition in noisy multi-channel environments","author":"Meyer","year":"2016","journal-title":"IEEE Workshop on Spoken Language Technology"},{"key":"10.1016\/j.heares.2017.12.014_bib29","series-title":"Proceedings IEEE Int. Conf. Acoust. Speech Signal Process. (ICASSP)","first-page":"4273","article-title":"Understanding how deep belief networks perform acoustic modelling","author":"Mohamed","year":"2012"},{"key":"10.1016\/j.heares.2017.12.014_bib30","series-title":"Proceedings INTERSPEECH 2016-17th Annual Conference of the International Speech Communication Association, San Francisco, USA","article-title":"On the role of nonlinear transformations in deep neural network acoustic models","author":"Nagamine","year":"2016"},{"key":"10.1016\/j.heares.2017.12.014_bib31","series-title":"Proceedings Eurospeech\u201903","first-page":"10","article-title":"Performance analysis of the Aurora large vocabulary baseline system","author":"Parihar","year":"2003"},{"issue":"6","key":"10.1016\/j.heares.2017.12.014_bib32","doi-asserted-by":"crossref","first-page":"2098","DOI":"10.1109\/TASL.2006.872621","article-title":"Improved signal-to-noise ratio estimation for speech enhancement","volume":"14","author":"Plapous","year":"2006","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"key":"10.1016\/j.heares.2017.12.014_bib33","series-title":"Proceedings IEEE 2011 Workshop on Automatic Speech Recognition and Understanding, ASRU","article-title":"The Kaldi speech recognition toolkit","author":"Povey","year":"2011"},{"key":"10.1016\/j.heares.2017.12.014_bib34","doi-asserted-by":"crossref","first-page":"2642","DOI":"10.1121\/1.4897398","article-title":"Listening effort and speech intelligibility in listening situations affected by noise and reverberation","volume":"136","author":"Rennies","year":"2014","journal-title":"J.\u00a0Acoust. Soc. Am."},{"issue":"4 Pt 1","key":"10.1016\/j.heares.2017.12.014_bib35","doi-asserted-by":"crossref","first-page":"2181","DOI":"10.1121\/1.1861713","article-title":"A\u00a0Speech Intelligibility Index-based approach to predict the speech reception threshold for sentences in fluctuating noise for normal-hearing listeners","volume":"117","author":"Rhebergen","year":"2005","journal-title":"J.\u00a0Acoust. Soc. Am."},{"key":"10.1016\/j.heares.2017.12.014_bib47","doi-asserted-by":"crossref","first-page":"1230","DOI":"10.1044\/1092-4388(2009\/08-0111)","article-title":"Objective measures of listening effort: effects of background noise and noise reduction","volume":"52","author":"Sarampalis","year":"2009","journal-title":"J.\u00a0Speech Lang. Hear. Res."},{"issue":"5","key":"10.1016\/j.heares.2017.12.014_bib36","doi-asserted-by":"crossref","first-page":"2708","DOI":"10.1121\/1.4948772","article-title":"A\u00a0simulation framework for auditory discrimination experiments: revealing the importance of across-frequency processing in speech perception","volume":"139","author":"Sch\u00e4dler","year":"2016","journal-title":"J.\u00a0Acoust. Soc. Am."},{"key":"10.1016\/j.heares.2017.12.014_bib37","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1016\/j.specom.2007.01.009","article-title":"Reaching over the gap: a review of efforts to link human and automatic speech recognition research","volume":"49","author":"Scharenborg","year":"2007","journal-title":"Speech Commun."},{"issue":"12","key":"10.1016\/j.heares.2017.12.014_bib38","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1080\/14992027.2016.1219774","article-title":"Perceived listening effort and speech intelligibility in reverberation and noise for hearing-impaired listeners","volume":"55","author":"Schepker","year":"2016","journal-title":"Int. J. Audiol."},{"key":"10.1016\/j.heares.2017.12.014_bib39","series-title":"Proceedings 8th EFAS Congress\/10th Congress of the German Society of Audiology","article-title":"Listening effort and speech intelligibility","author":"Schulte","year":"2007"},{"key":"10.1016\/j.heares.2017.12.014_bib40","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.csl.2017.10.004","article-title":"Predicting speech intelligibility with deep neural networks","volume":"48","author":"Spille","year":"2018","journal-title":"Comput. Speech Lang"},{"key":"10.1016\/j.heares.2017.12.014_bib41","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.specom.2004.11.009","article-title":"Human and machine consonant recognition","volume":"45","author":"Sroka","year":"2005","journal-title":"Speech Commun."},{"issue":"7","key":"10.1016\/j.heares.2017.12.014_bib42","doi-asserted-by":"crossref","first-page":"2125","DOI":"10.1109\/TASL.2011.2114881","article-title":"An algorithm for intelligibility prediction of time\u2013frequency weighted noisy speech","volume":"19","author":"Taal","year":"2011","journal-title":"IEEE Trans. Audio Speech Lang. Process."},{"key":"10.1016\/j.heares.2017.12.014_bib43","doi-asserted-by":"crossref","first-page":"2345","DOI":"10.21437\/Interspeech.2013-548","article-title":"Sequence-discriminative training of deep neural networks","volume":"2013","author":"Vesel\u00fd","year":"2013","journal-title":"Proc. INTERSPEECH"},{"key":"10.1016\/j.heares.2017.12.014_bib44","first-page":"4","article-title":"Entwicklung und Evaluation eines Satztests f\u00fcr die deutsche Sprache I: design des Oldenburger Satztests","volume":"38","author":"Wagener","year":"1999","journal-title":"Zeitschrift f\u00fcr Audiologie"},{"issue":"6","key":"10.1016\/j.heares.2017.12.014_bib45","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pone.0100186","article-title":"An eye-tracking paradigm for analyzing the processing time of sentences with different linguistic complexities","volume":"9","author":"Wendt","year":"2014","journal-title":"PLos One"},{"key":"10.1016\/j.heares.2017.12.014_bib46","series-title":"Achieving Human Parity in Conversational Speech Recognition","author":"Xiong","year":"2016"}],"container-title":["Hearing Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0378595517304951?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0378595517304951?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T00:09:33Z","timestamp":1719706173000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0378595517304951"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,3]]},"references-count":46,"alternative-id":["S0378595517304951"],"URL":"https:\/\/doi.org\/10.1016\/j.heares.2017.12.014","relation":{},"ISSN":["0378-5955"],"issn-type":[{"value":"0378-5955","type":"print"}],"subject":[],"published":{"date-parts":[[2018,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Single-ended prediction of listening effort using deep neural networks","name":"articletitle","label":"Article Title"},{"value":"Hearing Research","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.heares.2017.12.014","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2018 Elsevier B.V. All rights reserved.","name":"copyright","label":"Copyright"}]}}