Speech recognition in analog multichannel cochlear prostheses: initial experiments in controlling classifications

Abstract

Computer-synthesized vowels were used to examine methods for controlling and measuring the perceptions elicited during electrical stimulation of the human cochlea. In the first experiment, we measured the importance of the second formant (F2) in the identification of vowels, matched for duration, in a single subject with a multichannel cochlear implant. The subject never confused vowels having a "low" frequency F2 with those having a "high" frequency F2. In the second experiment, identification functions were generated for a series of vowels varying only in F2. When the pattern of F2 stimulation at the basilar membrane was manipulated, vowel identification functions were altered. For the categorization of vowels, the data indicate that the relative cochlear position of F2 stimulation was more important than fine-grain temporal waveform cues. The data are supportive of cochlear implant coding strategies that make use of cochlear place information. In the later experiments, we manipulated filter passbands and channel gains to explore their effect on these classifications. These preliminary studies indicate that it is possible to "fine-tune" such classifications.