Music Pre-Processing for Cochlear Implants

A Cochlear Implant (CI) is a medical device that enables profoundly hearing impaired people to perceive sounds by electrically stimulating the auditory nerve using an electrode array implanted in the cochlea. The focus of most research on signal processing for CIs has been on strategies to improve speech understanding in quiet and in background noise, since the main aim for implanting a CI was (and still is) to restore the ability to communicate. Most CI users perform quite well in terms of speech understanding. On the other hand, music perception and appreciation are generally very poor. The main goal of this PhD project was to investigate and to improve the poor music enjoyment in CI users. An initial experiment with multi-track recordings was carried out to examine the music mixing preferences for different instruments in polyphonic or complex music. In general, a preference for clear vocals and attenuated instruments was observed with preservation of bass and drums. Based on this knowledge, a music preprocessing scheme for mono and stereo recordings was developed which is capable of balancing vocals/bass/drums against the other instruments. The scheme is based on the representation of harmonic and percussive components in the spectrogram and on the spatial information of the instruments in typical stereo recordings. Subsequently, the music preprocessing scheme was evaluated in a take-home experiment with postlingually deafened CI users and different genres of music, providing encouraging results for building a tool for music training or rehabilitation programs.