Environmental noise suppression algorithms for hearing aids

针对先进的助听器，研究了抑制环境噪声的数字信号处理算法。对一个麦克风和两个麦克风的算法进行了研究，对于用一个麦克风抑制环境噪声的数字信号处理算法，谱减法是众所周知的，并且得到了广泛的应用。在该方法中，从输入信号的频谱中减去环境噪声的平均频谱。这种方法通常使用傅里叶变换来计算频谱。然而，传统的傅里叶变换谱减法性能不佳。因此，我们使用了小波变换，这被认为是类似于听觉系统中的频率分析过程。利用小波分析中的各种基函数，进行了听觉实验，评价了它们的性能。实验结果表明，非正交基函数比正交基函数具有更好的恢复清晰度的效果。其次，研究了双麦克风数字信号算法。当使用多个麦克风时，波束形成技术是最有前途的。虽然传统的波束形成技术对于自由或几乎自由的声场是有效的，但在现场或混响的房间中并不是非常有效。由于这种恶化是由直达声和反射之间的相位关系引起的，因此我们提出了一种新的波束形成算法，该算法不利用输入信号的相位关系，而是只关注其功率谱。新算法在频散声场中表现出比传统算法更好的性能。

Digital signal processing algorithms to suppress environmental noise were studied for advanced hearing aid. Algorithms with one microphone and two microphones were examined.As to digital signal processing algorithm to suppress environmental noise with one microphone, the spectral subtraction method is well known and widely used. In the method, averaged frequency spectrum of environmental noise is subtracted from the frequency spectrum of input signal. This method usually uses Fourier transform to calculate the frequency spectrum. The conventional spectrum subtraction with Fourier transform, however, gives insufficient performance. We, therefore, used wavelet transform, which was considered to be similar to the frequency analysis process in the auditory system. Using various kinds of basis functions for the wavelet analysis, hearing experiments were carried out to evaluate their performances. The result showed that the intelligibility was better restored with non-orthogonal basis functions than with orthogonal ones.Digital signal algorithms with two microphones were examined next. When multiple microphones are used, beam-forming techniques are the most promising. Though conventional beam-forming technique is effective for a free or almost free sound field, it is not very effective in a live or reverberant room. Since such deterioration is caused by the phase relation between of direct sound and reflections, we developed a new beam-forming algorithm which did not use phase relation of the input signal but focused only on its power spectrum. The new algorithm showed better performance in a dispersive sound field than the conventional alrorithm.