Multi-Head Attention and GRU for Improved Match-Mismatch Classification of Speech Stimulus and EEG Response
Marvin Borsdorf, Saurav Pahuja, Gabriel Ivucic, Siqi Cai, Haizhou Li, Tanja Schultz
Abstract
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.
Topics & Concepts
ElectroencephalographySpeech recognitionSpectrogramComputer scienceDecoding methodsStimulus (psychology)Speech processingArtificial intelligencePsychologyCognitive psychologyNeuroscienceTelecommunicationsBlind Source Separation TechniquesSpeech and Audio ProcessingAdvanced Adaptive Filtering Techniques