Details
| Original language | English |
|---|---|
| Title of host publication | 2022 7th International Conference on Frontiers of Signal Processing, ICFSP 2022 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 159-164 |
| Number of pages | 6 |
| ISBN (electronic) | 9781665481588 |
| ISBN (print) | 978-1-6654-8159-5 |
| Publication status | Published - 2022 |
| Event | 7th International Conference on Frontiers of Signal Processing, ICFSP 2022 - Paris, France Duration: 7 Sept 2022 → 9 Sept 2022 |
Publication series
| Name | 2022 7th International Conference on Frontiers of Signal Processing, ICFSP 2022 |
|---|
Abstract
Cochlear implants (CIs) are battery-powered, surgically implanted hearing-aids capable of restoring a sense of hearing in people suffering from moderate to profound hearing loss. To achieve this, audio signals captured by the microphone of the CI are processed by its signal processor and converted into electrical pulses, the stimulation patterns, which then excite certain areas of the cochlear. Nowadays wireless transmission of audio from external devices, like remote microphones and smartphones, is used to improve speech understanding and localization or for the convenience of the CI user. To conserve energy or channel capacity in this wireless transmission, data compression is commonly applied. In this work, zero delay lossless compression of the so called clinical units of the CIs is proposed and a zero delay lossless codec (ZDLLC) based on artificial neural networks is investigated for this purpose. The ZDLLC is compared to the lossless compression algorithms PAQ and PPM as well as the lossy Opus audio codec. On the TIMIT speech corpus and various acoustic scenarios the ZDLLC achieved a mean bitrate of 28.6 kbit/s at zero algorithmic latency compared to 33.6 kbit/s to 35.2 kbit/s for the Opus audio codec at 5 ms to 7.5 ms algorithmic latency. In contrast, at very high latency, PPM achieved a mean bitrate of 37.3 kbit/s and PAQ achieved a mean bitrate of 25.1 kbit/s. It was found that lossless compression of the stimulation patterns could be useful for wireless streaming of audio.
Keywords
- cochlear implants, lossless compression, neural networks
ASJC Scopus subject areas
- Computer Science(all)
- Computer Networks and Communications
- Computer Science(all)
- Signal Processing
Sustainable Development Goals
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2022 7th International Conference on Frontiers of Signal Processing, ICFSP 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 159-164 (2022 7th International Conference on Frontiers of Signal Processing, ICFSP 2022).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Lossless Compression at Zero Delay of the Electrical Stimulation Patterns of Cochlear Implants for Wireless Streaming of Audio Using Artificial Neural Networks
AU - Hinrichs, Reemt
AU - Ehmann, Lukas
AU - Heise, Hendrik
AU - Ostermann, Jorn
N1 - Funding Information: This work was supported by the DFG Cluster of Excellence EXC 1077/1 Hearing4all and funded by the German Research Foundation (DFG) - Project number: 381895691
PY - 2022
Y1 - 2022
N2 - Cochlear implants (CIs) are battery-powered, surgically implanted hearing-aids capable of restoring a sense of hearing in people suffering from moderate to profound hearing loss. To achieve this, audio signals captured by the microphone of the CI are processed by its signal processor and converted into electrical pulses, the stimulation patterns, which then excite certain areas of the cochlear. Nowadays wireless transmission of audio from external devices, like remote microphones and smartphones, is used to improve speech understanding and localization or for the convenience of the CI user. To conserve energy or channel capacity in this wireless transmission, data compression is commonly applied. In this work, zero delay lossless compression of the so called clinical units of the CIs is proposed and a zero delay lossless codec (ZDLLC) based on artificial neural networks is investigated for this purpose. The ZDLLC is compared to the lossless compression algorithms PAQ and PPM as well as the lossy Opus audio codec. On the TIMIT speech corpus and various acoustic scenarios the ZDLLC achieved a mean bitrate of 28.6 kbit/s at zero algorithmic latency compared to 33.6 kbit/s to 35.2 kbit/s for the Opus audio codec at 5 ms to 7.5 ms algorithmic latency. In contrast, at very high latency, PPM achieved a mean bitrate of 37.3 kbit/s and PAQ achieved a mean bitrate of 25.1 kbit/s. It was found that lossless compression of the stimulation patterns could be useful for wireless streaming of audio.
AB - Cochlear implants (CIs) are battery-powered, surgically implanted hearing-aids capable of restoring a sense of hearing in people suffering from moderate to profound hearing loss. To achieve this, audio signals captured by the microphone of the CI are processed by its signal processor and converted into electrical pulses, the stimulation patterns, which then excite certain areas of the cochlear. Nowadays wireless transmission of audio from external devices, like remote microphones and smartphones, is used to improve speech understanding and localization or for the convenience of the CI user. To conserve energy or channel capacity in this wireless transmission, data compression is commonly applied. In this work, zero delay lossless compression of the so called clinical units of the CIs is proposed and a zero delay lossless codec (ZDLLC) based on artificial neural networks is investigated for this purpose. The ZDLLC is compared to the lossless compression algorithms PAQ and PPM as well as the lossy Opus audio codec. On the TIMIT speech corpus and various acoustic scenarios the ZDLLC achieved a mean bitrate of 28.6 kbit/s at zero algorithmic latency compared to 33.6 kbit/s to 35.2 kbit/s for the Opus audio codec at 5 ms to 7.5 ms algorithmic latency. In contrast, at very high latency, PPM achieved a mean bitrate of 37.3 kbit/s and PAQ achieved a mean bitrate of 25.1 kbit/s. It was found that lossless compression of the stimulation patterns could be useful for wireless streaming of audio.
KW - cochlear implants
KW - lossless compression
KW - neural networks
UR - http://www.scopus.com/inward/record.url?scp=85142387565&partnerID=8YFLogxK
U2 - 10.1109/ICFSP55781.2022.9924629
DO - 10.1109/ICFSP55781.2022.9924629
M3 - Conference contribution
AN - SCOPUS:85142387565
SN - 978-1-6654-8159-5
T3 - 2022 7th International Conference on Frontiers of Signal Processing, ICFSP 2022
SP - 159
EP - 164
BT - 2022 7th International Conference on Frontiers of Signal Processing, ICFSP 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Frontiers of Signal Processing, ICFSP 2022
Y2 - 7 September 2022 through 9 September 2022
ER -