Accurate Estimation of Compression in Simultaneous Masking Enables the Simulation of Hearing Impairment for Normal-Hearing Listeners

This chapter presents a unified gammachirp framework for estimating cochlear compression and synthesizing sounds with inverse compression that cancels the compression of a normal-hearing (NH) listener to simulate the experience of a hearing-impaired (HI) listener. The compressive gammachirp (cGC) filter was fitted to notched-noise masking data to derive level-dependent filter shapes and the cochlear compression function (e.g., Patterson et al., J Acoust Soc Am 114:1529-1542, 2003). The procedure is based on the analysis/synthesis technique of Irino and Patterson (IEEE Trans Audio Speech Lang Process 14:2222-2232, 2006) using a dynamic cGC filterbank (dcGC-FB). The level dependency of the dcGC-FB can be reversed to produce inverse compression and resynthesize sounds in a form that cancels the compression applied by the auditory system of the NH listener. The chapter shows that the estimation of compression in simultaneous masking is improved if the notched-noise procedure for the derivation of auditory filter shape includes noise bands with different levels. Since both the estimation and resynthesis are performed within the gammachirp framework, it is possible for a specific NH listener to experience the loss of a specific HI listener.