Suppr超能文献

交错声环境:听觉场景分类程序对人工耳蜗使用者言语感知的影响。

Interleaved Acoustic Environments: Impact of an Auditory Scene Classification Procedure on Speech Perception in Cochlear Implant Users.

机构信息

Audiological Acoustics, ENT Department, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany.

出版信息

Trends Hear. 2021 Jan-Dec;25:23312165211014118. doi: 10.1177/23312165211014118.

Abstract

Clinical speech perception tests with simple presentation conditions often overestimate the impact of signal preprocessing on speech perception in complex listening environments. A new procedure was developed to assess speech perception in interleaved acoustic environments of different complexity that allows investigation of the impact of an automatic scene classification (ASC) algorithm on speech perception. The procedure was applied in cohorts of normal hearing (NH) controls and uni- and bilateral cochlear implant (CI) users. Speech reception thresholds (SRTs) were measured by means of a matrix sentence test in five acoustic environments that included different noise conditions (amplitude modulated and continuous), two spatial configurations, and reverberation. The acoustic environments were encapsulated in a randomized, mixed order single experimental run. Acoustic room simulation was played back with a loudspeaker auralization setup with 128 loudspeakers. 18 NH, 16 unilateral, and 16 bilateral CI users participated. SRTs were evaluated for each individual acoustic environment and as mean-SRT. Mean-SRTs improved by 2.4 dB signal-to-noise ratio for unilateral and 1.3 dB signal-to-noise ratio for bilateral CI users with activated ASC. Without ASC, the mean-SRT of bilateral CI users was 3.7 dB better than the SRT of unilateral CI users. The mean-SRT indicated significant differences, with NH group performing best and unilateral CI users performing worse with a difference of up to 13 dB compared to NH. The proposed speech test procedure successfully demonstrated that speech perception and benefit with ASC depend on the acoustic environment.

摘要

临床语音感知测试采用简单的呈现条件,往往会高估信号预处理对复杂聆听环境下语音感知的影响。本研究开发了一种新的程序,用于评估不同复杂程度的交错声学环境中的语音感知,从而可以研究自动场景分类(ASC)算法对语音感知的影响。该程序应用于正常听力(NH)对照组和单侧及双侧人工耳蜗植入(CI)使用者队列。通过矩阵句子测试,在包含不同噪声条件(调幅和连续)、两种空间配置和混响的五种声学环境中测量语音接收阈值(SRT)。这些声学环境被封装在一个随机、混合顺序的单个实验运行中。使用带有 128 个扬声器的扬声器听觉化设置播放声学房间模拟。18 名 NH 参与者、16 名单侧 CI 使用者和 16 名双侧 CI 使用者参与了研究。为每个个体声学环境和平均 SRT 评估 SRT。激活 ASC 后,单侧 CI 用户的 SRT 平均提高了 2.4dB 信噪比,双侧 CI 用户的 SRT 平均提高了 1.3dB 信噪比。没有 ASC,双侧 CI 用户的平均 SRT 比单侧 CI 用户的 SRT 好 3.7dB。平均 SRT 表明存在显著差异,NH 组表现最好,单侧 CI 用户表现最差,与 NH 相比,差异最大可达 13dB。所提出的语音测试程序成功地证明了语音感知和 ASC 的获益取决于声学环境。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/99ae/8150447/e4b960427ec0/10.1177_23312165211014118-fig1.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验