Design a New Speech Encoder for Cochlear Implants Using DRNL model presentation
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Design a New Speech Encoder for Cochlear Implants Using DRNL model.

Agenda:
Introduction.
Cochlear implant devices.
Methodologies.
Comparisons.
Proposed methodology.
Conclusion.

Introduction

Today, a prosthetic device, called cochlear implant, can be implanted in the inner ear and can restore partial hearing to profoundly deaf people.
Prosthetic device processors utilize the channel vocoder .





C.I Devices

Methodologies
Single Channel implants:
It provide electrical stimulation at a single site in the cochlea using a single electrode. Different methods in single channel implants are:

House/3M single-channel implant &
Developed: William House
Electrodes: 22
Vienna/3M single-channel implant.
Developed: Technical University of Vienna




Multiple Channel implants:

Multi-channel implants provide electrical stimulation at multiple sites in the cochlea using an array of electrodes. Different methods in multi channel implants are:
Compressed analog (CA) approach.
Continuous interleaved sampling (CIS) approach.




Compressed analog approach

Device: Ineraid manufactured by Symbion.

Signal compressed using automatic gain control.
Filtered into four continuous frequency bands.
Sent through adjustable gain control.
Directly sent to electrodes.
Waveforms delivered to each electrode simultaneously in analog form.




Continuous interleaved sampling

Device : Clarion device, the Med-El device, and the new Nucleus CI24M device.
Research Triangle Institute (RTI) developed the Continuous Interleaved Sampling (CIS) approach .
Signal is pre emphasized & passed through BPF.
Filtered waveforms are extracted by rectification & LPF.
At last the signals are compared and used to biphasic pulses.





Comparisons


Disadvantage:

Interaction between channels.







Advantage over C.A:

Non-simultaneous stimulation.
Use of six channels rather than four.
Disadvantage:
Performance is less in noisy conditions.


Proposed methodologies

The dual-resonance nonlinear filter was presented as a digital time-domain algorithm to model nonlinear auditory frequency selectivity.
A DRNL model was adopted because it is simpler than other adaptive nonlinear models of the basilar membrane and can be readily integrated into the CI speech processor.

Decomposition

Center frequencies .

Gain & Bandwidth also changes.




Input to both paths is the same & equal to x(t).
The transfer function of the DRNL filter can be expressed as the sum of the individual transfer functions of its two paths, HL( f ) and HN( f ).

Conclusion

Cochlear implants have been very successful in restoring partial hearing to profoundly deaf people.


By using DRNL model for CI may produces better speech perception under noise conditions.
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