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人工耳蜗使用者的听力努力:语音清晰度、降噪处理和工作记忆容量对瞳孔扩张反应的影响。

Listening Effort in Cochlear Implant Users: The Effect of Speech Intelligibility, Noise Reduction Processing, and Working Memory Capacity on the Pupil Dilation Response.

作者信息

Dingemanse Gertjan, Goedegebure André

机构信息

Department of Otorhinolaryngology, Head and Neck Surgery, Erasmus University Medical Center, Rotterdam, the Netherlands.

出版信息

J Speech Lang Hear Res. 2022 Jan 12;65(1):392-404. doi: 10.1044/2021_JSLHR-21-00230. Epub 2021 Dec 13.

Abstract

PURPOSE

This study aimed to evaluate the effect of speech recognition performance, working memory capacity (WMC), and a noise reduction algorithm (NRA) on listening effort as measured with pupillometry in cochlear implant (CI) users while listening to speech in noise.

METHOD

Speech recognition and pupil responses (peak dilation, peak latency, and release of dilation) were measured during a speech recognition task at three speech-to-noise ratios (SNRs) with an NRA in both on and off conditions. WMC was measured with a reading span task. Twenty experienced CI users participated in this study.

RESULTS

With increasing SNR and speech recognition performance, (a) the peak pupil dilation decreased by only a small amount, (b) the peak latency decreased, and (c) the release of dilation after the sentences increased. The NRA had no effect on speech recognition in noise or on the peak or latency values of the pupil response but caused less release of dilation after the end of the sentences. A lower reading span score was associated with higher peak pupil dilation but was not associated with peak latency, release of dilation, or speech recognition in noise.

CONCLUSIONS

In CI users, speech perception is effortful, even at higher speech recognition scores and high SNRs, indicating that CI users are in a chronic state of increased effort in communication situations. The application of a clinically used NRA did not improve speech perception, nor did it reduce listening effort. Participants with a relatively low WMC exerted relatively more listening effort but did not have better speech reception thresholds in noise.

摘要

目的

本研究旨在评估语音识别性能、工作记忆容量(WMC)和降噪算法(NRA)对人工耳蜗(CI)使用者在噪声环境中听语音时通过瞳孔测量法测得的听觉努力程度的影响。

方法

在语音识别任务中,分别在三种信噪比(SNR)条件下,测量开启和关闭NRA时的语音识别和瞳孔反应(峰值扩张、峰值潜伏期和扩张释放)。通过阅读跨度任务测量WMC。20名有经验的CI使用者参与了本研究。

结果

随着信噪比和语音识别性能的提高,(a)瞳孔峰值扩张仅略有下降,(b)峰值潜伏期缩短,(c)句子结束后的扩张释放增加。NRA对噪声环境中的语音识别或瞳孔反应的峰值或潜伏期值没有影响,但在句子结束后导致的扩张释放较少。较低的阅读跨度得分与较高的瞳孔峰值扩张相关,但与峰值潜伏期、扩张释放或噪声环境中的语音识别无关。

结论

在CI使用者中,即使在较高的语音识别分数和高信噪比下,语音感知也很费力,这表明CI使用者在交流情境中处于长期的努力增加状态。临床使用的NRA的应用并没有改善语音感知,也没有减少听觉努力。WMC相对较低的参与者付出的听觉努力相对较多,但在噪声环境中的语音接收阈值并没有更好。

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