cochlear implant/musical instrument identification (Rebecca Danielle Reich )

Subject: cochlear implant/musical instrument identification
From:    Rebecca Danielle Reich  <rreich(at)MIT.EDU>
Date:    Tue, 22 Jan 2002 16:03:00 -0500

Dear list, [apologies for the long post] I am a Master's degree student investigating the basic signal processing of a cochlear implant (specifically, the Clarion CIS strategy) to try to determine what cues used to identify musical instruments are being lost in the processing. The signal processing I am simulating consists of 1 to 8 channels of logarithmically-spaced bandpass filters, full-wave rectification and smoothing (a moving-average lowpass filter). I am creating sinusoids at the frequencies of the center frequencies of the bandpass filters and summing up the signal to deliver to normal-hearing listeners over headphones (this simulation is similar to Loizou's simulation,, but with different parameters). I plan on running test audio signals through the simulations and presenting the output signals to normal-hearing listeners over headphones. I would like to investigate more than just the number of channels required to achieve an acceptable (say, 70%) recognition rate; I would also like to find out more specifically what information is being lost to be able to suggest a better processing scheme for music signals. My question is: what would be the best type of audio signals to use for this experiment? I am limiting my signals to solo instruments, and was thinking along the lines of 5-note ascending/descending scales (to have note transitions and not isolated tones). Would synthetic instruments be cleaner and thus simpler to use than acoustic? Would a simpler experiment using only synthesized tones yield more insight? I am having trouble correlating the information I would like to obtain with the signals I need to use in order to obtain that information. I would appreciate any suggestions on input signals or experiment design. Thank you, Rebecca Rebecca Reich Music, Mind and Machine Group MIT Media Lab O: 617.253.6469 H: 617.225.9869 C: 617.407.0831

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