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Decoding Auditory EEG Responses using an Adapted WaveNet

Bob M.S.L. Van Dyck (KU Leuven); Liuyin Yang (KU Leuven); Marc Van Hulle (KU Leuven)

DOI
10.17023/qzma-v523
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10 Jun 2023

We introduce a WaveNet-based model that placed second in the Auditory EEG Challenge on the regression subtask of the ICASSP Signal Processing Grand Challenge 2023. The model achieved the highest score on the held-out subjects test set with 341k trainable parameters. In this paper, we present our network architecture, and training strategies along with a short discussion.

Tags:
Signal Processing for Communications and Networking

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