Cochlear implant (CI) patients have difficulty understanding tonal languages which use pitch variations to convey meaning because of poor pitch perception. The ability of CI patients to communicate in noisy environments is severely degraded. Therefore, pitch-detection and (spatial) noise suppression is of importance to current cochlear implant devices. This thesis provides the details of real-time implementations that address these concerns. A pitch-detector was implemented to estimate the pitch and a beamformer was implemented to suppress spatial noise. The pitch-detection and the beamforming algorithms were implemented on an ARM based processor of a Personal Digital Assistant (PDA). The pitch-detection algorithm is based on the autocorrelation function. Its real-time performance was measured and its efficiency in the presence of speech-shaped noise and babble noise was evaluated. The beamforming algorithm implemented was the Griffith’s beamformer. Objective and subjective tests for different signal-to-noise ratio levels of speech-shaped noise were conducted to evaluate its performance. This thesis includes the results of these evaluations.

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