The speech understanding capabilities of cochlear implant (Cl) users have increased steadily throughout the years. However, speech perception performance of Cl users drops tremendously in noisy listening conditions. Also, Cl users are unable to identify familiar melodies and enjoy music. Some Cl patients refer to music as """"""""noise with rhythm"""""""". Communicating in noise and enjoying music still remain the two biggest challenges in cochlear implants. Little is known about the factors that contribute to the poor performance of Cl users in noise and in identifying familiar melodies. In this project, we propose a series of experiments aimed at isolating these factors. We propose new signal processing algorithms tailored for music and noise. The proposed experiments have five specific aims.
The first aim assesses the relative contribution of fine structure and envelope information on word recognition in noise.
The second aim i nvestigates the performance of two noise reduction algorithms that preserve fine temporal cues and/or envelope cues. A method for customizing and optimizing the noise reduction algorithms to individual users is proposed.
The third aim assesses the relative contribution of fine structure and envelope information on melody recognition. ? The fourth aim investigates the performance of a new strategy that incorporates fine-structure information for better music perception. The last aim investigates the performance of a desynchronizing strategy which can be used for subjects who would otherwise not be able to receive any benefit from the strategies proposed in the previous aims for speech or music. The five aims taken together will produce speech/music coding algorithms that will be optimally fit to individual users. The results of the above experiments will lay the groundwork for a better understanding on the importance of fine structure cues for speech understanding in noise and for music appreciation by Cl listeners. It will also open new avenues for the development of future signal processing strategies for cochlear implants that could potentially be used to improve not only speech intelligibility but also speaker identification and tonal language recognition. ? ?

National Institute of Health (NIH)
National Institute on Deafness and Other Communication Disorders (NIDCD)
Research Project (R01)
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Special Emphasis Panel (ZDC1-SRB-W (42))
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Miller, Roger
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University of Texas-Dallas
Engineering (All Types)
Schools of Engineering
United States
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Falk, Tiago H; Parsa, Vijay; Santos, João F et al. (2015) Objective Quality and Intelligibility Prediction for Users of Assistive Listening Devices. IEEE Signal Process Mag 32:114-124
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Hu, Yi; Loizou, Philipos C (2010) Environment-specific noise suppression for improved speech intelligibility by cochlear implant users. J Acoust Soc Am 127:3689-95

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