针对助听器回声路径快速变化下易产生啸叫的问题,本文提出一种变步长标准最小均方差-陷波器(Variable Step Normalized least mean square-Notch Filter,VSN-NF)算法。在回声路径相对稳定时,提出一种基于状态分类的变步长标准最小均方差算法来估计回声信号。算法根据滤波器系数能量的长时平均值和短时平均值,将滤波器当前状态分为收敛态、过渡态与稳态,并根据不同状态选择不同的步长。在路径突然变化并产生啸叫时,算法通过关闭变步长NLMS算法来稳定啸叫频点,然后基于ZoomFFT算法动态生成陷波器来进行啸叫抑制;当啸叫抑制后,再开启变步长NLMS进行回声估计。针对易产生多频点啸叫的回声路径,VSN-NF算法还引入不同频带的两个陷波器来进行双频点啸叫抑制。同其它助听器回声抵消算法的对比实验显示,VSN-NF算法的回波抵消性能最好,尤其具有快速啸叫抑制能力。此外,算法生成的语音质量较高,实时性能好,适合于像助听器类的低功耗、小体积产品。
To alleviate the conflict between audibility and distortion in the conventional loudness compensation method, an adaptive multichannel loudness compensation method is proposed for hearing aids. The linear and wide dynamic range compression （WDRC） methods are alternately employed according to the dynamic range of the band-passed signal and the hearing range （HR） of the patient. To further reduce the distortion caused by the WDRC and improve the output signal to noise ratio （SNR） under noise conditions, an adaptive adjustment of the compression ratio is presented. Experimental results demonstrate that the output SNR of the proposed method in babble noise is improved by at least 1.73 dB compared to the WDRC compensation method, and the average speech intelligibility is improved by 6.0% and 5. 7%, respectively, compared to the linear and WDRC compensation methods.
