A Speech Processing Strategy based on Sinusoidal Speech Model for Cochlear Implant Users

In sinusoidal modeling(SM), speech signal, which is pseudo-periodic in structure, can be approximated by sinusoids and noise without losing significant speech information. A speech processing strategy based on this sinusoidal speech model will be relevant for encoding electric pulse streams in cochlear implant (CI) processing, where the number of channels available is limited. In this study, 5 normal hearing(NH) listeners and 2 CI users were asked to perform the task of speech recognition and perceived sound quality rating on speech sentences processed in 12 different test conditions. The sinusoidal analysis/synthesis algorithm was limited to 1, 3 or 6 sinusoids from the sentences low-pass filtered at either 1 kHz, 1.5 kHz, 3 kHz, or 6 kHz, re-synthesized as the test conditions. Each of 12 lists of AzBio sentences was randomly chosen and process with one of 12 test conditions, before they were presented to each participant at 65 dB SPL (Sound Pressure Level). Participant was instructed to repeat the sentence as they perceived, and the number of words correctly recognized was scored. They were also asked to rate the perceived sound quality of the sentences including original speech sentence, on the scale of 1 (distorted) to 10 (clean). Both speech recognition score and perceived sound quality rating across all participants increase when the number of sinusoids increases and low-pass filter broadens. Our current finding showed that three sinusoids may be sufficient to elicit the nearly maximum speech intelligibility and quality necessary for both NH and CI listeners. Sinusoidal speech model has the potential in facilitating the basis for a speech processing strategy in CI.