A brain-inspired algorithm improves "cocktail party" listening for individuals with hearing loss.

Alexander D Boyd, Virginia Best, Kamal Sen
{"title":"A brain-inspired algorithm improves \"cocktail party\" listening for individuals with hearing loss.","authors":"Alexander D Boyd, Virginia Best, Kamal Sen","doi":"10.1038/s44172-025-00414-5","DOIUrl":null,"url":null,"abstract":"<p><p>Selective listening in competing-talker situations is an extraordinarily difficult task for many people. For individuals with hearing loss, this difficulty can be so extreme that it seriously impedes communication and participation in daily life. Directional filtering is one of few proven methods to improve speech understanding in competition, and most hearing devices now incorporate some kind of directional technology, although real-world benefits are modest, and many approaches fail in competing-talker situations. We recently developed a biologically inspired algorithm that is capable of very narrow spatial tuning and can isolate one talker from a mixture of talkers. The algorithm is based on a hierarchical network model of the auditory system, in which binaural sound inputs drive populations of neurons tuned to specific spatial locations and frequencies, and the spiking responses of neurons in the output layer are reconstructed into audible waveforms. Here we evaluated the algorithm in a group of adults with sensorineural hearing loss, using a challenging competing-talker task. The biologically inspired algorithm led to robust intelligibility gains under conditions in which a standard beamforming approach failed. The results provide compelling support for the potential benefits of biologically inspired algorithms for assisting individuals with hearing loss in \"cocktail party\" situations.</p>","PeriodicalId":72644,"journal":{"name":"Communications engineering","volume":"4 1","pages":"75"},"PeriodicalIF":0.0000,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12015318/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1038/s44172-025-00414-5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Selective listening in competing-talker situations is an extraordinarily difficult task for many people. For individuals with hearing loss, this difficulty can be so extreme that it seriously impedes communication and participation in daily life. Directional filtering is one of few proven methods to improve speech understanding in competition, and most hearing devices now incorporate some kind of directional technology, although real-world benefits are modest, and many approaches fail in competing-talker situations. We recently developed a biologically inspired algorithm that is capable of very narrow spatial tuning and can isolate one talker from a mixture of talkers. The algorithm is based on a hierarchical network model of the auditory system, in which binaural sound inputs drive populations of neurons tuned to specific spatial locations and frequencies, and the spiking responses of neurons in the output layer are reconstructed into audible waveforms. Here we evaluated the algorithm in a group of adults with sensorineural hearing loss, using a challenging competing-talker task. The biologically inspired algorithm led to robust intelligibility gains under conditions in which a standard beamforming approach failed. The results provide compelling support for the potential benefits of biologically inspired algorithms for assisting individuals with hearing loss in "cocktail party" situations.

一种受大脑启发的算法改善了听力损失患者的“鸡尾酒会”听力。
对许多人来说,在交谈激烈的情况下有选择地倾听是一项非常困难的任务。对于有听力损失的人来说,这种困难可能非常严重,严重阻碍了日常生活的交流和参与。定向过滤是为数不多的在比赛中提高语音理解的行之有效的方法之一,大多数听力设备现在都采用了某种定向技术,尽管现实世界的好处并不大,而且许多方法在比赛中都失败了。我们最近开发了一种受生物学启发的算法,它能够进行非常窄的空间调谐,并能从一群说话者中分离出一个说话者。该算法基于听觉系统的分层网络模型,其中双耳声音输入驱动调谐到特定空间位置和频率的神经元群,输出层神经元的尖峰响应被重构为可听波形。在这里,我们在一组有感觉神经性听力损失的成年人中评估了该算法,使用了一个具有挑战性的竞争谈话任务。在标准波束形成方法失败的情况下,受生物学启发的算法导致了鲁棒的可理解性增益。这些结果为生物学启发的算法在“鸡尾酒会”情况下帮助听力损失的个人的潜在好处提供了令人信服的支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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:481959085
Book学术官方微信