TY  - JOUR
A1  - Stober, Sebastian
T1  - Toward Studying Music Cognition with Information Retrieval Techniques: Lessons Learned from the OpenMIIR Initiative
JF  - Frontiers in psychology
N2  - As an emerging sub-field of music information retrieval (MIR), music imagery information retrieval (MIIR) aims to retrieve information from brain activity recorded during music cognition-such as listening to or imagining music pieces. This is a highly interdisciplinary endeavor that requires expertise in MIR as well as cognitive neuroscience and psychology. The OpenMIIR initiative strives to foster collaborations between these fields to advance the state of the art in MIIR. As a first step, electroencephalography (EEG) recordings ofmusic perception and imagination have beenmade publicly available, enabling MIR researchers to easily test and adapt their existing approaches for music analysis like fingerprinting, beat tracking or tempo estimation on this new kind of data. This paper reports on first results of MIIR experiments using these OpenMIIR datasets and points out how these findings could drive new research in cognitive neuroscience.
KW  - music cognition
KW  - music perception
KW  - music information retrieval
KW  - deep learning
KW  - representation learning
Y1  - 2017
U6  - https://doi.org/10.3389/fpsyg.2017.01255
SN  - 1664-1078
VL  - 8
PB  - Frontiers Research Foundation
CY  - Lausanne
ER  - 
TY  - JOUR
A1  - Stober, Sebastian
T1  - Toward Studying Music Cognition with Information Retrieval Techniques
BT  - Lessons Learned from the OpenMIIR Initiative
JF  - Frontiers in psychology
N2  - As an emerging sub-field of music information retrieval (MIR), music imagery information retrieval (MIIR) aims to retrieve information from brain activity recorded during music cognition–such as listening to or imagining music pieces. This is a highly inter-disciplinary endeavor that requires expertise in MIR as well as cognitive neuroscience and psychology. The OpenMIIR initiative strives to foster collaborations between these fields to advance the state of the art in MIIR. As a first step, electroencephalography (EEG) recordings of music perception and imagination have been made publicly available, enabling MIR researchers to easily test and adapt their existing approaches for music analysis like fingerprinting, beat tracking or tempo estimation on this new kind of data. This paper reports on first results of MIIR experiments using these OpenMIIR datasets and points out how these findings could drive new research in cognitive neuroscience.
KW  - music cognition
KW  - music perception
KW  - music information retrieval
KW  - deep learning
KW  - representation learning
Y1  - 2017
U6  - https://doi.org/10.3389/fpsyg.2017.01255
SN  - 1664-1078
VL  - 8
PB  - Frontiers Research Foundation
CY  - Lausanne
ER  -