Intel Neuromorphic Deep Noise Suppression Challenge The Intel Neuromorphic Deep Noise Suppression Challenge has begun!
Here the fundamental computation will be built on temporally sparse event codes to drastically reduce power requirements to be deployed on dedicated HW (expected about 10x-100x savings compared to other dedicated ASICs). Deep Noise Suppression is a ubiquitous real-time audio processing task with low power and imperceptible latency. A neuromorphic solution offering >10x lower power and smaller model sizes could extend battery lives, improve user experiences, and help shrink form factors of many PC/mobile/wearable devices. We are reiterating on the Microsoft Deep Noise suppression re-framing it into *Neuromorphic computing,* offering a novel neuromorphic baseline example improving on SI-SNR and reducing memory footprint by ~20x on previous MSFT DNS 2022 Challenge Baseline. If you can come up with the best algorithmic solution in simulation within six months or the best Loihi 2 demonstration within a year, you could win $15k and $40k respectively. (See challenge rules for details.) For more information, see: Paper: https://arxiv.org/abs/2303.09503 GitHub: https://github.com/IntelLabs/IntelNeuromorphicDNSChallenge [image: u/dinatrina - [N] Intel Neuromorphic Deep Noise Suppression Challenge] <https://preview.redd.it/51zkapmugpqa1.png?width=800&format=png&auto=webp&v=enabled&s=c3efb228c0a45997e74951a737cf251d7b76c0cf>
