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Clairaudience claimed the top $15,000 prize for the Intel Neuromorphic Deep Noise Suppression (NDNS) Challenge, . 19 models from 8 teams were evaluated for algorithmic innovation using an audio denoising dataset of human speech including English, German, French, Spanish, Russian and various categories of noise. The winning team’s submission improved audio quality by up to 8 dB using a novel Gated Spiking Unit neuron model, a sophisticated network architecture integrating both full-band and sub-band processing modules, and adversarial training techniques rarely applied so far in the neuromorphic field (winning presentation).
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