Signal processing strategies for better melody recognition and improved speech understanding in noise for cochlear implants

Cochlear implants are prosthetic devices, consisting of implanted electrodes and a signal processor and are designed to restore partial hearing to the profoundly deaf community. Since their inception in early 1970s cochlear implants have gradually gained popularity and consequently considerable research has been done to advance and improve the cochlear implant technology. Most of the research conducted so far in the field of cochlear implants has been primarily focused on improving speech perception in quiet. Music perception and speech perception in noisy listening conditions with cochlear implants are still highly challenging problems. Many research studies have reported low recognition scores in the task of simple melody recognition. Most of the cochlear implant devices use envelope cues to provide electric stimulation. Understanding the effect of various factors on melody recognition in the context of cochlear implants is important to improve the existing coding strategies. In the present work we investigate the effect of various factors such as filter spacing, relative phase, spectral up-shifting, carrier frequency and phase perturbation on melody recognition in acoustic hearing. The filter spacing currently used in the cochlear implants is larger than the musical semitone steps and hence not all musical notes can be resolved. In the current work we investigate the use of new filter spacing techniques called the 'Semitone filter spacing techniques' in which filter bandwidths are varied in correspondence to the musical semitone steps. Noise reduction methods investigated so far for use with cochlear implants are mostly pre-processing methods. In these methods, the speech signal is first enhanced using the noise reduction method and the enhanced signal is then processed using the speech processor. A better and more efficient approach is to integrate the noise reduction mechanism into the cochlear implant signal processing. In this dissertation we investigate the use of two such embedded noise reduction methods namely, the 'SNR weighting method' and the 'S-shaped compression' to improve speech perception in noisy listening conditions. The SNR weighting noise reduction method is an exponential weighting method that uses the instantaneous signal to noise ratio (SNR) estimate to perform noise reduction in each frequency band that corresponds to a particular electrode in the cochlear implant. The S-shaped compression technique divides the compression curve into two regions based on the noise estimate. This method applies a different type of compression for the noise portion and the speech portion and hence better suppresses the noise compared to the regular power-law compression.