Using blind source separation techniques to improve speech recognition in bilateral cochlear implant patients

Bilateral cochlear implants seek to restore the advantages of binaural hearing by improving access to binaural cues. Bilateral implant users are currently fitted with two processors, one in each ear, operating independent of one another. In this work, a different approach to bilateral processing is explored based on blind source separation (BSS) by utilizing two implants driven by a single processor. Sentences corrupted by interfering speech or speech-shaped noise are presented to bilateral cochlear implant users at 0 dB signal-to-noise ratio in order to evaluate the performance of the proposed BSS method. Subjects are tested in both anechoic and reverberant settings, wherein the target and masker signals are spatially separated. Results indicate substantial improvements in performance in both anechoic and reverberant settings over the subjects' daily strategies for both masker conditions and at various locations of the masker. It is speculated that such improvements are due to the fact that the proposed BSS algorithm capitalizes on the variations of interaural level differences and interaural time delays present in the mixtures of the signals received by the two microphones, and exploits that information to spatially separate the target from the masker signals.