ANALYSIS OF SPEECH PROCESSING STRATEGIES FOR THE CLARION IMPLANT PROCESSOR

Author: Mishra, Lakshmi Narayan
Advisor: Philip Loizou
URL: http://www.utdallas.edu/~loizou/thesis/mishra_ms_thesis.pdf

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http://www.utdallas.edu/~loizou/thesis/mishra_ms_thesis.pdf
Completion Date: January 2000
Degree: M.Sc./M.A.
Institution: University of Texas at Dallas
Abstract: The variability in patient performance noticed in cochlear implant users demands the development of new and improved speech processing strategies that will help improve speech recognition for poor users of the device. The Clarion cochlear implant has various parameters that can be manipulated and Clarion patients can be fitted with several speech processing strategies. In this thesis, the Clarion research interface was used to evaluate the performance of commercially available as well as new speech processing strategies. Six different strategies were implemented and tested with 12 Clarion implant patients (10 CIS users and 2 SAS users). The six different strategies included three commercially available strategies (CIS, PPS and SAS) and three new (not commercially available in the Clarion device) strategies: the hybrid, quadruple pulsatile sampler (QPS) and the 6-of-8 strategy. These strategies differed in the degree of simultaneity and rate of stimulation. Speech recognition results showed that the performance obtained with the CIS strategy was not statistically different with the performance obtained with the PPS, QPS, the hybrid strategies in quiet, and with the 6-of-8 strategy in noise. There was a large variability in performance among subjects. In noise, some subjects benefited with the 6-of-8 strategy. In quiet, some subjects obtained higher performance with the PPS, QPS and the hybrid strategies compared to the CIS strategy. We believe that this variability was due to the amount of channel interaction. Subjects with small channel interaction are most likely to benefit with the high rates of stimulation provided by the PPS and QPS strategies. Further research is needed to identify the various factors that affect implant users' performance.