基于光学麦克风的语音重建系统与深度学习,用于有听力损失的个人
IEEE transactions on bio-medical engineering
|June 16, 2023
概括
本研究介绍了一种使用光学麦克风的新型深度学习语音增强 (SE) 方法. 这种方法显著提高了听力障碍患者的语音质量和可理解性,即使有背景噪音和距离干扰.
科学领域:
- 生物医学工程 生物医学工程
- 信号处理 信号处理
- 听力科学 听力科学
背景情况:
- 传统的语音增强 (SE) 方法与非静止噪音和远程扬声器作斗争.
- 现有的SE算法往往无法在具有挑战性的声学环境中充分改善听力障碍患者的语音感知.
研究的目的:
- 克服传统语音增强方法的局限性.
- 开发一种新的SE方法,能够提高听力障碍者的语音质量和可理解性.
主要方法:
- 提出了一个基于深度学习的SE方法.
- 集成了一个光学麦克风来捕获目标扬声器音频.
- 该方法对七种典型的听力损失类型进行了评估.
主要成果:
- 提出的方法在客观评估中显著超过了基线方法.
- 在语音质量 (HASQI) 中观察到0.21-0.27的改善,在语音理解/可理解性 (HASPI) 中观察到0.34-0.64的改善.
- 该方法有效地降低了噪音,并减轻了与距离相关的干扰.
结论:
- 拟议的基于深度学习的SE方法通过过噪音和补偿距离来增强语音感知.
- 这种方法提供了一个有前途的解决方案,以改善听力障碍患者的听力体验.
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