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Effect of Time Constant on Speech Enhancement in Hearing Aids Based on Auditory Neural Feedback

机译:基于听觉神经反馈的时间常数对助听器语音增强的影响

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The medial olivocochlear neuron feedback loop in the human auditory system plays a critical role in speech-in-noise perception. Recent studies have successfully simulated the mechanism of the neuron feedback and developed corresponding speech enhancement algorithms for hearing applications. These algorithms apply time-varying attenuation to hearing applications by reducing the gain in each frequency band over time. The speed of gain reduction is characterized by a time constant. In hearing applications, it is known that speech intelligibility is related to the gain regulating time constant. However, the effect of the time constant on enhancement performance is unclear. This paper studies its effect on speech intelligibility in hearing aids by incorporating a time constant variable speech enhancement algorithm modified from an existing neuron feedback model into a hearing aid model. The study demonstrates intelligibility improvement of over 30% at SNR between 5 and 10 dB. The longer time constants (≥ 1000 ms) show greater intelligibility improvement (about 20%) at SNR ≤ 10 dB, whilst the shorter time constants show more benefits at SNR > 10 dB.
机译:人类听觉系统中的内侧小腱鞘神经元反馈回路在语音中的噪声感知中起着至关重要的作用。最近的研究已经成功地模拟了神经元反馈的机制,并开发了用于听力应用的相应语音增强算法。这些算法通过随时间减少每个频段的增益,将时变衰减应用于听力应用。增益降低的速度以时间常数为特征。在听力应用中,众所周知,语音清晰度与增益调节时间常数有关。但是,时间常数对增强性能的影响尚不清楚。本文通过将时间常数变量语音增强算法(从现有的神经元反馈模型修改为助听器模型)来研究其对助听器语音清晰度的影响。该研究表明,在5至10 dB的SNR时,清晰度提高了30%以上。较长的时间常数(≥1000 ms)在SNR≤10 dB时显示出更好的清晰度(约20%),而较短的时间常数在SNR> 10 dB时显示出更多的好处。

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