汉语数字助听器高频听损增强方法的实验研究

Experimental study on enhancement method for high-frequency hearing loss in Chinese digital hearing aids

提出采用正弦模型改善患者高频听觉的非线性降频方法。正弦模型语音分解得到的幅度、频率和相位是算法三个主要的处理参数。为了避免谱失真,将语音频谱按倍频程划分为6个部分。最接近并低于患者门限频率的部分,只做幅度放大处理。按照不同频段对于语音理解度的贡献程度,将患者门限频率以上的频率段压缩并转移到患者的可听频段,并将对应相位信息变为最接近的对应低频相位。在本研究中,10个受试者进行了语音理解度测试。测试结果显示,经过训练后,患者的平均理解率至少提高45%。下一步的研究应增加受试者数量,并增加对患者的听损情况的详细分析,从而设计出更合理,更细致的降频助听算法。

A nonlinear frequency lowering algorithm based on the sinusoidal speech model is proposed to improve high-frequency audibility. In a sinusoidal model, the speech waveform can be characterized by the amplitudes, frequencies, and phases of the component sine waves. These parameters are main processing objects in the study. The frequency spectrum is split into six parts according to octaves to avoid spectral distortions in the sounds. For the part which is below and closest to a threshold frequency of the patient, only the amplitudes amplification method is used. Frequencies above a threshold frequency are compressed by different ratios according to the speech intelligibility in different frequency ranges and shifted to the remaining regions below the threshold frequency. Phases of the transformed frequency are adjusted to the same as the phases of the low-frequency closest to this frequency. In this study, ten subjects were tested. Results in the speech recognition experiment show the mean speech intelligibility is improved with at least 45% after the training of five weeks. In future, the number of subjects should be increased. Furthermore, hearing loss characteristics of different patients should be carefully analysised to design a more reasonable and more detailed frequency lowering algorithm.