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Updated: Sep 10, 2025

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Neuro-rehabilitation Approach for Sudden Sensorineural Hearing Loss
Published on: January 25, 2016
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听力受损的听众的组合降噪和动态范围压缩的偏好和相似性
Niels Overby1, Torsten Dau1, Pavel Zahorik2
1Hearing Systems Group, Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark.
The Journal of the Acoustical Society of America
|August 21, 2025
概括
基于深度神经网络的单通道降噪 (SCNR) 提高了助听器的性能. 用SCNR进行场景感应的压缩几乎与在噪音中进行理想压缩一样受欢迎.
科学领域:
- 听力学
- 信号处理
- 人工智能
背景情况:
- 助听器使用单通道降噪 (SCNR) 和宽动态范围压缩 (WDRC) 来提高语音听力.
- SCNR和WDRC可能会产生负面相互作用,可能会减少轻声语音或放大噪音.
- 深度神经网络 (DNN) 提供先进的降噪功能.
研究的目的:
- 基于深度神经网络 (DNN) 的单通道降噪 (SCNR) 的宽动态范围压缩 (WDRC) 配置的行为评估.
- 为了比较不同的WDRC策略,包括快速作用,缓慢作用和场景感知压缩.
- 在各种处理条件下评估用户对噪声的偏好和相似性.
主要方法:
- 16名听力受损的参与者使用对比任务评估了WDRC系统.
- 系统包括基于DNN的SCNR和没有DNN的快速起作用,缓慢起作用和现场感知WDRC.
- 一个具有快速作用的压缩和噪声/反响减弱的"理想"系统作为参考.
主要成果:
- 在所有测试的WDRC配置中,基于DNN的SCNR显著改善了听众的偏好.
- 理想的系统得到了最高的偏好.
- 当与DNN-SCNR相结合时,场景感知和缓慢作用的WDRC显示出接近理想系统的偏好分数.
结论:
- 基于DNN的SCNR提高了助听器压缩策略的性能.
- 场景感知压缩,加上有效的降噪,提供与理想处理相美的高质量听觉体验.
- 这些发现表明助听器信号处理的最佳方法可以最大限度地提高用户的满意度.
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