The long-term goal of this research is to improve cochlear implant patient performance by maximizing both the transmission and reception of acoustic patterns. We hypothesize that, due to the loss of fine spectral details, cochlear implant patients have great difficulty in challenging listening conditions (e.g., noise, competing speech, reverberation, unfamiliar talkers, etc.). We propose to optimize the input acoustic signal in response to the acoustic environment, or to different speaker characteristics, thereby improving the transmission of speech patterns. We further hypothesize that poor patient performance may be partly due to sub-optimal settings of important speech processor parameters (e.g., stimulation mode, frequency allocation, stimulation rate, etc.). We propose to optimize these parameters according to individual patients'psychophysical capabilities, thereby improving the reception of speech patterns. Combining these two approaches - pre-processing the input signal and optimizing processor parameters - will provide the greatest benefit to patient performance for a variety of listening conditions. There are three specific aims in the proposed research.
Specific aim 1 is to improve the transmission of acoustic patterns. We will evaluate novel speech enhancement algorithms that optimize the input acustic patterns in response to the acoustic environment, or to different speaker characteristics.
Specific aim 2 is to improve the reception of acoustic patterns. We will explore the perceptual space for important speech processor parameters and optimize these parameters according to individual patients'psychophysical capabilities.
Specific aim 3 is to evaluate the long-term effects of changes to speech processing. While we will generally study the effects of each optimization technique independently in each experiment, the techniques can be easily combined to further optimize audio processing for cochlear implants, once the parameter space is defined. Each of the proposed strategies seeks to optimize some aspect of speech processing and, when combined, the benefit from one strategy may be directly enhanced by the benefit from another. This synergy may further improve patient performance for a wide variety of listening conditions. The proposed research is of great clinical importance in terms of maximizing patient performance under a variety of listening conditions. It is also of great theoretical interest in terms of understanding the neural and perceptual mechanisms involved in pattern recognition.
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