噪音和混响中的双耳语音清晰度:正常听力和听力受损听众群体表现的预测。

IF 3 2区 医学 Q1 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY
Trends in Hearing Pub Date : 2025-01-01 Epub Date: 2025-05-28 DOI:10.1177/23312165251344947
Raphael Cueille, Mathieu Lavandier
{"title":"噪音和混响中的双耳语音清晰度:正常听力和听力受损听众群体表现的预测。","authors":"Raphael Cueille, Mathieu Lavandier","doi":"10.1177/23312165251344947","DOIUrl":null,"url":null,"abstract":"<p><p>A binaural model is proposed to predict speech intelligibility in rooms for normal-hearing (NH) and hearing-impaired listener groups, combining the advantages of two existing models. The <i>leclere2015</i> model takes binaural room impulse responses (BRIRs) as inputs and accounts for the temporal smearing of the speech by reverberation, but only works with stationary noises for NH listeners. The <i>vicente2020</i> model takes the speech and noise signals at the ears as well as the listener audiogram as inputs and accounts for modulations in the noise and hearing loss, but cannot predict the temporal smearing of the speech by reverberation. The new model takes the audiogram, BRIRs and ear signals as inputs to account for the temporal smearing of the speech, the masker modulations and hearing loss. It gave accurate predictions for speech reception thresholds measured in seven experiments. The proposed model can do predictions that neither of the two original models can make when the target speech is influenced by reverberation and the noise has modulations and/or the listeners have hearing loss. In terms of model parameters, four methods were compared to separate the early and late reverberation, and two methods were compared to account for hearing loss.</p>","PeriodicalId":48678,"journal":{"name":"Trends in Hearing","volume":"29 ","pages":"23312165251344947"},"PeriodicalIF":3.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12120292/pdf/","citationCount":"0","resultStr":"{\"title\":\"Binaural Speech Intelligibility in Noise and Reverberation: Prediction of Group Performance for Normal-hearing and Hearing-impaired Listeners.\",\"authors\":\"Raphael Cueille, Mathieu Lavandier\",\"doi\":\"10.1177/23312165251344947\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A binaural model is proposed to predict speech intelligibility in rooms for normal-hearing (NH) and hearing-impaired listener groups, combining the advantages of two existing models. The <i>leclere2015</i> model takes binaural room impulse responses (BRIRs) as inputs and accounts for the temporal smearing of the speech by reverberation, but only works with stationary noises for NH listeners. The <i>vicente2020</i> model takes the speech and noise signals at the ears as well as the listener audiogram as inputs and accounts for modulations in the noise and hearing loss, but cannot predict the temporal smearing of the speech by reverberation. The new model takes the audiogram, BRIRs and ear signals as inputs to account for the temporal smearing of the speech, the masker modulations and hearing loss. It gave accurate predictions for speech reception thresholds measured in seven experiments. The proposed model can do predictions that neither of the two original models can make when the target speech is influenced by reverberation and the noise has modulations and/or the listeners have hearing loss. In terms of model parameters, four methods were compared to separate the early and late reverberation, and two methods were compared to account for hearing loss.</p>\",\"PeriodicalId\":48678,\"journal\":{\"name\":\"Trends in Hearing\",\"volume\":\"29 \",\"pages\":\"23312165251344947\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12120292/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Trends in Hearing\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/23312165251344947\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/5/28 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Trends in Hearing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/23312165251344947","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/28 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

结合两种模型的优点,提出了一种双耳模型来预测正常听力人群和听障人群的语音清晰度。leclere2015模型采用双耳房间脉冲响应(brir)作为输入,并考虑了混响对语音的时间干扰,但仅适用于NH听众的固定噪声。vicente2020模型将耳朵中的语音和噪声信号以及听者听图作为输入,并考虑了噪声和听力损失中的调制,但无法预测混响对语音的时间干扰。新模型将听力图、brir和耳信号作为输入,以解释语音的时间模糊、掩模调制和听力损失。它对七个实验中测量的语音接收阈值给出了准确的预测。当目标语音受混响影响、噪声有调制和/或听者有听力损失时,所提出的模型可以做出两种原始模型都无法做出的预测。在模型参数方面,比较了四种分离早、晚混响的方法,比较了两种考虑听力损失的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Binaural Speech Intelligibility in Noise and Reverberation: Prediction of Group Performance for Normal-hearing and Hearing-impaired Listeners.

Binaural Speech Intelligibility in Noise and Reverberation: Prediction of Group Performance for Normal-hearing and Hearing-impaired Listeners.

Binaural Speech Intelligibility in Noise and Reverberation: Prediction of Group Performance for Normal-hearing and Hearing-impaired Listeners.

Binaural Speech Intelligibility in Noise and Reverberation: Prediction of Group Performance for Normal-hearing and Hearing-impaired Listeners.

A binaural model is proposed to predict speech intelligibility in rooms for normal-hearing (NH) and hearing-impaired listener groups, combining the advantages of two existing models. The leclere2015 model takes binaural room impulse responses (BRIRs) as inputs and accounts for the temporal smearing of the speech by reverberation, but only works with stationary noises for NH listeners. The vicente2020 model takes the speech and noise signals at the ears as well as the listener audiogram as inputs and accounts for modulations in the noise and hearing loss, but cannot predict the temporal smearing of the speech by reverberation. The new model takes the audiogram, BRIRs and ear signals as inputs to account for the temporal smearing of the speech, the masker modulations and hearing loss. It gave accurate predictions for speech reception thresholds measured in seven experiments. The proposed model can do predictions that neither of the two original models can make when the target speech is influenced by reverberation and the noise has modulations and/or the listeners have hearing loss. In terms of model parameters, four methods were compared to separate the early and late reverberation, and two methods were compared to account for hearing loss.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Trends in Hearing
Trends in Hearing AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGYOTORH-OTORHINOLARYNGOLOGY
CiteScore
4.50
自引率
11.10%
发文量
44
审稿时长
12 weeks
期刊介绍: Trends in Hearing is an open access journal completely dedicated to publishing original research and reviews focusing on human hearing, hearing loss, hearing aids, auditory implants, and aural rehabilitation. Under its former name, Trends in Amplification, the journal established itself as a forum for concise explorations of all areas of translational hearing research by leaders in the field. Trends in Hearing has now expanded its focus to include original research articles, with the goal of becoming the premier venue for research related to human hearing and hearing loss.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信