One of the ambitions of computational musicology con-sists in characterising music harmony in a symbolic system. In the context of the EU project Polifonia, we are exploring the possibility to associate EEG data to charac-terise harmony from a cognitive and emotional point of view. Data will be collected using a Brain Computer In-terface (BCI). In a further step, we aim to train a ML classifier to automate the pattern recognition process. To obtain the EEG characterisation, we will consider chord sequences. This choice represents per sè a novelty, considering that in literature mainly sounds and tracks have been explored with BCI interfaces. We present preliminary findings and on that basis sketch research hy-potheses to be further developed.
A chord progression library for measuring emotions by BCIs / R. Folgieri, E. Daga, C. Lucchiari, P. Arnold. ((Intervento presentato al 23. convegno International Society for Music Information Retrieval ConferenceI-SMIR 2022 tenutosi a Bengaluru nel 2022.
A chord progression library for measuring emotions by BCIs
R. Folgieri;C. Lucchiari;
2022
Abstract
One of the ambitions of computational musicology con-sists in characterising music harmony in a symbolic system. In the context of the EU project Polifonia, we are exploring the possibility to associate EEG data to charac-terise harmony from a cognitive and emotional point of view. Data will be collected using a Brain Computer In-terface (BCI). In a further step, we aim to train a ML classifier to automate the pattern recognition process. To obtain the EEG characterisation, we will consider chord sequences. This choice represents per sè a novelty, considering that in literature mainly sounds and tracks have been explored with BCI interfaces. We present preliminary findings and on that basis sketch research hy-potheses to be further developed.File | Dimensione | Formato | |
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