通过双路循环神经网络降噪方法,提高了触觉语音对背景噪声的强度
Mark D Fletcher1,2, Samuel W Perry3,4, Iordanis Thoidis5
1University of Southampton Auditory Implant Service, University of Southampton, University Road, Southampton, SO17 1BJ, UK. M.D.Fletcher@soton.ac.uk.
Scientific reports
|March 29, 2024
概括
触觉助听器使用振动来帮助人们在噪音中理解语音. 一个新的双路循环神经网络 (DPRNN) 通过触摸显著改善了语音感知,提供了更好的听力辅助.
科学领域:
- 生物医学工程 生物医学工程
- 声学 声学 在声学方面
- 信号处理 信号处理
背景情况:
- 听力损失在杂的环境中显著损害了语音理解,需要强大的助听器.
- 触觉助听器将声音转换为振动,帮助耳植入物 (CI) 用户和无法使用传统设备的个人.
- 与头戴式选项相比,身体上戴的触觉设备为先进的降噪技术提供了更多的空间.
研究的目的:
- 评估实时双路循环神经网络 (DPRNN) 对增强触觉语音噪音感知的有效性.
- 为了比较DPRNN的降噪能力与传统的方法,如日志-MMSE.
主要方法:
- 使用语音编码器将语音信号转换为手腕上的触觉振动,使用或不使用基于DPRNN的降噪.
- 使用尺度不变的信号与扭曲比率 (SI-SDR) 进行了客观评估.
- 行为评估涉及16名参与者,他们用2.5dB的信号对噪声比率在多个说话者噪声中识别出句子.
主要成果:
- DPRNN在SI-SDR中取得了8.6dB的改进,显著超过了日志-MMSE方法.
- 参与者通过DPRNN系统在仅触觉的句子识别准确度上表现出8.2%的改善.
- 结果表明,DPRNN在改善触觉助听器性能方面有很大的潜力.
结论:
- 像DPRNN这样的先进的降噪技术可以显著提高触觉助听器中的语音在噪声中的性能.
- 使用DPRNN的触觉器件可以作为对耳植入物有价值的补充或替代物,对于那些不符合CI.
- 这项技术有望为有听力损失的人提供更好的可访问性和结果.
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