Vector-Quantized Feedback Recurrent Autoencoders for the Compression of the Stimulation Patterns of Cochlear Implants at Zero Delay

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Original languageEnglish
Title of host publication2023 24th International Conference on Digital Signal Processing
Subtitle of host publicationDSP
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (electronic)9798350339598
ISBN (print)979-8-3503-3960-4
Publication statusPublished - 2023
Event24th International Conference on Digital Signal Processing, DSP 2023 - Rhodes, Greece
Duration: 11 Jun 202313 Jun 2023

Publication series

NameInternational Conference on Digital Signal Processing, DSP
Volume2023-June
ISSN (Print)1546-1874
ISSN (electronic)2165-3577

Abstract

Cochlear Implants (CIs) are surgically implanted hearing devices that allow to restore a sense of hearing in people suffering from moderate to profound hearing loss. Modern CIs offer wireless streaming of audio to the signal processor of the CI to improve speech understanding in complex acoustic environments. To conserve energy in this wireless streaming, proprietary source coding of the stimulation patterns of CIs was proposed, achieving state-of-the-art results with respect to bitrate, latency and intelligibility of the coded stimulation patterns. This work investigates vector-quantized feedback recurrent autoencoders (VQ FRAE) to improve source coding of the stimulation patterns of CIs. The VQ FRAE is optimized with respect to the non-differentiable STOI using simultaneous perturbation stochastic approximation. With this approach, a state-of-the-art bitrate of 4.69 kbit/s was achieved, while maintaining zero latency and little to no degredation of intelligibility. The FRAE outperforms audio codecs like Opus with respect to bitrate, intelligibility and latency.

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Vector-Quantized Feedback Recurrent Autoencoders for the Compression of the Stimulation Patterns of Cochlear Implants at Zero Delay. / Hinrichs, Reemt; Bilsky, Julian; Ostermann, Jorn.
2023 24th International Conference on Digital Signal Processing: DSP. Institute of Electrical and Electronics Engineers Inc., 2023. (International Conference on Digital Signal Processing, DSP; Vol. 2023-June).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Hinrichs, R, Bilsky, J & Ostermann, J 2023, Vector-Quantized Feedback Recurrent Autoencoders for the Compression of the Stimulation Patterns of Cochlear Implants at Zero Delay. in 2023 24th International Conference on Digital Signal Processing: DSP. International Conference on Digital Signal Processing, DSP, vol. 2023-June, Institute of Electrical and Electronics Engineers Inc., 24th International Conference on Digital Signal Processing, DSP 2023, Rhodes, Greece, 11 Jun 2023. https://doi.org/10.1109/DSP58604.2023.10167999
Hinrichs, R., Bilsky, J., & Ostermann, J. (2023). Vector-Quantized Feedback Recurrent Autoencoders for the Compression of the Stimulation Patterns of Cochlear Implants at Zero Delay. In 2023 24th International Conference on Digital Signal Processing: DSP (International Conference on Digital Signal Processing, DSP; Vol. 2023-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/DSP58604.2023.10167999
Hinrichs R, Bilsky J, Ostermann J. Vector-Quantized Feedback Recurrent Autoencoders for the Compression of the Stimulation Patterns of Cochlear Implants at Zero Delay. In 2023 24th International Conference on Digital Signal Processing: DSP. Institute of Electrical and Electronics Engineers Inc. 2023. (International Conference on Digital Signal Processing, DSP). doi: 10.1109/DSP58604.2023.10167999
Hinrichs, Reemt ; Bilsky, Julian ; Ostermann, Jorn. / Vector-Quantized Feedback Recurrent Autoencoders for the Compression of the Stimulation Patterns of Cochlear Implants at Zero Delay. 2023 24th International Conference on Digital Signal Processing: DSP. Institute of Electrical and Electronics Engineers Inc., 2023. (International Conference on Digital Signal Processing, DSP).
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AU - Bilsky, Julian

AU - Ostermann, Jorn

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AB - Cochlear Implants (CIs) are surgically implanted hearing devices that allow to restore a sense of hearing in people suffering from moderate to profound hearing loss. Modern CIs offer wireless streaming of audio to the signal processor of the CI to improve speech understanding in complex acoustic environments. To conserve energy in this wireless streaming, proprietary source coding of the stimulation patterns of CIs was proposed, achieving state-of-the-art results with respect to bitrate, latency and intelligibility of the coded stimulation patterns. This work investigates vector-quantized feedback recurrent autoencoders (VQ FRAE) to improve source coding of the stimulation patterns of CIs. The VQ FRAE is optimized with respect to the non-differentiable STOI using simultaneous perturbation stochastic approximation. With this approach, a state-of-the-art bitrate of 4.69 kbit/s was achieved, while maintaining zero latency and little to no degredation of intelligibility. The FRAE outperforms audio codecs like Opus with respect to bitrate, intelligibility and latency.

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