Acoustic simulations of cochlear implants in human and machine hearing research

In this chapter, we review conventional uses of acoustic simulations in cochlear implants research and introduce novel applications of acoustic simulations of cochlear implants, both in cochlear implants research and in other domains, such as automatic speech recognition (ASR) research. In this respect, the first part of the chapter is dedicated in reviewing the conventional applications of acoustic simulations in cochlear implants research. Actually, acoustic simulations are used in two typical applications in the research of cochlear implants. In the first one, acoustic simulations of cochlear implants are used to define how many independent channels are needed in order to achieve high levels of speech understanding? (Loizou et al., 1999). In fact, it is difficult to answer this question basing on the results of subjective tests performed by cochlear implant users, since their performance might be affected by many cofounding factors (e.g. number of surviving ganglion cells). For example, if a cochlear implant user obtains poor auditory performance using 4 channels of stimulation, the rationale might be that 4 stimulating channels are not enough but it could probably be blamed for the lack of surviving ganglion cells near the stimulating electrodes (Loizou et al., 1999). Using acoustic simulations can help in separating the rationale coming from the lack of surviving ganglion cells. The second application of acoustic simulations in cochlear implants research is for determining the effect of electrode insertion depth on speech understanding. In cochlear implantation, electrode arrays are inserted only partially to the cochlea, typically 22-30 mm, depending on the state of the cochlea. Acoustic simulations of cochlear implants could be used to simulate the effect of depth of electrode insertion on identification accuracy. In this respect, normal hearing listeners performed identification tasks with an acoustic simulation of cochlear implant whose electrodes are separated by 4 mm (Dorman et al., 1997). Insertion depth was simulated by outputting sine waves from each channel of the processor at a frequency determined by the cochlear place of electrode inserted 22-25 mm into the cochlea, through the Greenwood’s frequency-to-place equation (Greenwood, 1990). The results indicated that simulated insertion depth had a significant effect on speech identification performance (Dorman et al., 1997).