1. Relationship between perception of spectral ripple and speech recognition in cochlear implant and vocoder listeners L.M. Litvak, A.J. Spahr, A.A. Saoji, and G.Y. Fridman

2. Relationship between perception of spectral ripple and speech recognition in cochlear implant and vocoder listeners Frequency (Hz)

3. Cochlear Implant users Variability Why? Can we explain this variability by testing normal listeners? Where an explanation arise? Start from the beginning – the stimulation point.

4. Cochlear Implant: Auditory Nerve – Electric fields, overlap = distortion Normal Listener: Basilar membrane – Auditory filters, spread = decreased spectral resolution Stimulation point Frequency (Hz) Spectral Level Frequency (Hz) Spectral Level How do we change the spectral resolution in normal listeners?

5. Vocoder Simulations Vocoder – electronic device that synthesizes speech Vocoder Simulations – Reduces spectral information to 15 channels Mimics CI processing – Drop-off varied 5 – 40 dB/octave Mimics variable spectral resolution How do we measure the changes in normal listeners? Frequency (Hz)

6. Perception of Spectral Ripple How well can we represent spectral information in speech? += Frequency (Hz)Spectral Level

7. Spectral modulation threshold Spectral modulation threshold (SMT) – measure of spectral resolution – measures the spectral ripple perception Will the varied spectral resolution demonstrate the same variability seen in CI word recognition scores?

8. L.M. Litvak, A.J. Spahr, A.A. Saoji, and G.Y. Fridman Relationship between perception of spectral ripple and speech recognition in cochlear implant and vocoder listeners

9. Methods 25 CI users, 10 normal listeners Normal listeners – Vocoder simulations Speech – Separated in 15 bands – Multiplied by noise – Change rate of drop-off of noise spectrum » Varies spread Tested for recognition of vowels and consonants Compare word recognition scores Frequency (Hz)

10. Results: Vowels

11. Results: Consonants

12. Primarily spectral cues Primarily Temporal / Amplitude

13. Results Normal listeners – SMT increase = decrease in word recognition scores (WRS) – Decrease in WRS similar to CI listeners with similar SMTs Variability in spread (due to SMT increase) of neural activity largely accounts for variability in CI users scores.

14. Conclusions Main Finding: – Same slope between CI and normal listeners Spectral resolution = explanation of variability in CI users Subsidiary Finding: – Differences between vowels and consonants Temporal cues

15. Questions Additional Factors – Age of subjects Alternative explanations – Other cues besides temporal cues – Frequency to place alignment problem Central plasticity

17. Confusion Matrix: Vowels

18. Confusion Matrix: Consonants