Print Email Facebook Twitter Music identification using brain responses to initial snippets Title Music identification using brain responses to initial snippets Author Pandey, Pankaj (Indian Institute of Technology Gandhinagar) Sharma, Gulshan (Indian Institute of Technology Ropar) Miyapuram, Krishna P. (Indian Institute of Technology Gandhinagar) Subramanian, Ramanathan (University of Canberra) Lomas, J.D. (TU Delft Design Aesthetics) Date 2022 Abstract Naturalistic music typically contains repetitive musical patterns that are present throughout the song. These patterns form a signature, enabling effortless song recognition. We investigate whether neural responses corresponding to these repetitive patterns also serve as a signature, enabling recognition of later song segments on learning initial segments. We examine EEG encoding of naturalistic musical patterns employing the NMED-T and MUSIN-G datasets. Experiments reveal that (a) training machine learning classifiers on the initial 20s song segment enables accurate prediction of the song from the remaining segments; (b) β and γ band power spectra achieve optimal song classification, and (c) listener-specific EEG responses are observed for the same stimulus, characterizing individual differences in music perception. Subject music perceptionNeural signaturesrepetitive musical patternssong identification To reference this document use: http://resolver.tudelft.nl/uuid:a5b53b09-9aa7-4f53-a0eb-c59bf07a3b61 DOI https://doi.org/10.1109/ICASSP43922.2022.9747332 Publisher IEEE, Piscataway,NJ, USA Embargo date 2023-07-01 ISBN 978-1-6654-0540-9 Source 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings Event 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022, 2022-05-23 → 2022-05-27, Virtual, Online, Singapore Series ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, 1520-6149, 2022-May Bibliographical note Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. Part of collection Institutional Repository Document type conference paper Rights © 2022 Pankaj Pandey, Gulshan Sharma, Krishna P. Miyapuram, Ramanathan Subramanian, J.D. Lomas Files PDF Music_Identification_Usin ... ippets.pdf 10.61 MB Close viewer /islandora/object/uuid:a5b53b09-9aa7-4f53-a0eb-c59bf07a3b61/datastream/OBJ/view