Multi-Head Attention and GRU for Improved Match-Mismatch Classification of Speech Stimulus and EEG Response
Marvin Borsdorf (University of Bremen); Saurav Pahuja (University of Bremen); Gabriel Ivucic (University of Bremen); Siqi Cai (National University of Singapore); Haizhou Li (The Chinese University of Hong Kong, Shenzhen); Tanja Schultz (University of Bremen)
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10 Jun 2023
This work is based on the participation by the HyperAttention team in the Auditory EEG Decoding Challenge, 2023 (ICASSP 2023 Signal Processing Grand Challenge) task 1, which deals with the match-mismatch classification of speech stimuli and EEG responses of human listeners. We demonstrate the benefits of using mel-spectrograms instead of speech envelopes as input features as well as the effectiveness of Multi-Head Attention and GRU for EEG and speech processing. With a total score of 79.05 %, we reach the second place in the challenge.
