Neural Encoding of Songs is Modulated by Their Enjoyment

Gulshan Sharma, Pankaj Pandey, Ramanathan Subramanian, Krishna Prasad Miyapuram, Abhinav Dhall

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review

1 Citation (Scopus)


We examine user and song identification from neural (EEG) signals. Owing to perceptual subjectivity in human-media interaction, music identification from brain signals is a challenging task. We demonstrate that subjective differences in music perception aid user identification, but hinder song identification. In an attempt to address intrinsic complexities in music identification, we provide empirical evidence on the role of enjoyment in song recognition. Our findings reveal that considering song enjoyment as an additional factor can improve EEG-based song recognition.

Original languageEnglish
Title of host publicationICMI 2022 - Proceedings of the 2022 International Conference on Multimodal Interaction
PublisherAssociation for Computing Machinery, Inc
Number of pages6
ISBN (Electronic)9781450393904
Publication statusPublished - 7 Nov 2022
Event24th ACM International Conference on Multimodal Interaction, ICMI 2022 - Bangalore, India
Duration: 7 Nov 202211 Nov 2022

Publication series

NameACM International Conference Proceeding Series


Conference24th ACM International Conference on Multimodal Interaction, ICMI 2022
Abbreviated titleICMI 2022
Internet address


Dive into the research topics of 'Neural Encoding of Songs is Modulated by Their Enjoyment'. Together they form a unique fingerprint.

Cite this