Wavelet-based nonlinear AGC method for hearing aid loudness compensation

Hearing impairment can often be corrected by medical or surgical treatment, provided the loss is not due to cochlear pathology (sensorineural loss). For sensorineural loss, the only corrective action is to wear a hearing aid. Many perceptual differences between normal and sensorineural hearing-impaired listeners are due to differences in the dB levels at which sound is detected by the ear (auditory threshold) and the associated dynamic range over which it is comfortable to listen to (loudness sensation). To adequately compensate for this, the processing of the auditory signal should be nonlinear and time-varying. Two wavelet-based compression algorithms have been developed: automatic gain control (AGC) with linear amplification and nonlinear compression AGC. The nonlinear AGC is a compression algorithm, which models loudness sensation. The wavelet transform separates the input into seven frequency bands corresponding to the critical bands of the human auditory system. For each frequency band, multiplying the wavelet coefficients by the gain can amplify or compress nonlinearly and smoothly, depending on the signal level, time and spectrum. Results suggest that the nonlinear approach, while maintaining the general spectral structure of the signal, is perceptually superior to linear AGC and compensates better for audibility loss.