Learning a song: an ACT-R model

dc.contributor.authorChikhaoui, Belkacem
dc.contributor.authorPigot, Hélene
dc.contributor.authorBeaudoin, Mathieu
dc.contributor.authorPratte, Guillaume
dc.contributor.authorETAL.
dc.date.accessioned2022-12-12T08:36:26Z
dc.date.accessioned2023-08-19T08:19:11Z
dc.date.available2022-12-12T08:36:26Z
dc.date.available2023-08-19T08:19:11Z
dc.date.issued2009-08
dc.description.abstractThe way music is interpreted by the human brain is a very interesting topic, but also an intricate one. Although this domain has been studied for over a century, many gray areas remain in the understanding of music. Recent advances have enabled us to perform accurate measurements of the time taken by the human brain to interpret and assimilate a sound. Cognitive computing provides tools and development environments that facilitate human cognition simulation. ACT-R is a cognitive architecture which offers an environment for implementing human cognitive tasks. This project combines our understanding of the music interpretation by a human listener and the ACT-R cognitive architecture to build SINGER, a computerized simulation for listening and recalling songs. The results are similar to human experimental data. Simulation results also show how it is easier to remember short melodies than long melodies which require more trials to be recalled correctly.en_US
dc.identifier.citationChikhaoui, B., Pigot, H., Beaudoin, M., Pratte, G., Bellefeuille, P., & Laudares, F. (2009). Learning a song: an ACT-R model. International Journal of Computer and Information Engineering, 3(7), 1784-1789.en_US
dc.identifier.urihttps://edms.wexl.in/handle/1/4121
dc.language.isoenen_US
dc.subjectACT-R modelen_US
dc.subjectMusicen_US
dc.subjectDataen_US
dc.subjectHuman brainen_US
dc.titleLearning a song: an ACT-R modelen_US
dc.title.alternativeInternational Journal of Computer and Information Engineeringen_US
dc.typeArticleen_US

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