The 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.
[1] G. D. Sawa, "Oral transmission in arabic music, past and present," Oral
Tradition Journal, vol. 4/1-2, pp. 254-265, 1989.
[2] A. Racette and I. Peretz, "Learning lyrics: to sing or not to sing?"
Memory & Cognition Journal, vol. 35 (2), pp. 242-253, 2007.
[3] J. W. Stansell, "The use of music in learning languages: A review of the
literature," University of Illinois at Urbana-Champaign, M.Ed., 2005.
[4] M. L. Huy, "The role of music in second language learning: A vietnamese
perspective," in Conference of the Australian Association for
Research in Education and the New Zealand Association for Research
in Education, 1999.
[5] G. Mather, Foundations of Perception. Psychology Pr, 2006.
[6] C.-H. Chouard, L-oreille musicienne. Les chemins de la musique de
l-oreille au cerveau. Gallimard, 2001.
[7] J. Plantinga and L. J. Trainor, "Memory for melody: infants use a relative
pitch code," Cognition Journal, vol. 98, pp. 1-11, 2004.
[8] W. Gruhn and F. H. Rauscher, The Neurobiology of Learning: New
Approaches to Music Pedagogy Conclusions and Implications, nova ed.,
ser. Neurosciences in Music Pedagogy, 2007, ch. 10, pp. 263-295.
[9] V. J. Williamson, A. D. Baddeley, and G. J. Hitch, "Music in working
memory? examining the effect of pitch proximity on the recall
performance of nonmusicians." 9th International Conference on Music
Perception and Cognition, pp. 1581-1590, 2006.
[10] J. R. Anderson, D. Bothell, M. D. Byrne, S. Douglass, C. Lebiere, and
Y. Qin, "An integrated theory of the mind," Psychological Review, vol.
111, 136-1060, 2004.
[11] J. R. Anderson, N. A. Taatgen, and M. D. Byrne, "Learning to achieve
perfect time sharing: Architectural implications of hazeltine, teague ivry
(2002)," Journal of Experimental Psychology: Human Perception and
Performance, vol. 31, No. 4, pp. 749-761, 2005.
[12] M. D. Byrne, "Act-r/pm and menu selection: Applying a cognitive
architecture to hci," International Journal of Human-Computer Studies,
vol. 55, pp. 41-84, 2001.
[13] D. Bothell, "Act-r 6.0 reference manual," Carnegie Mellon University,
Working Draft, 2004.
[14] J. R. Anderson, D. Bothell, C. Lebiere, and M. Matessa, "An integrated
theory of list memory," Journal of Memory and Language, vol. 38, no. 4,
pp. 341-380, 1998.
[15] I. Peretz and R. Zatorre, "Brain organization for music processing,"
Annual Review of Psychology, vol. 56, pp. 89-114, 2005.
[16] N. Gaab, C. Gaser, T. Zaehle, L. Jancke, and G. Schlaug, "Functional
anatomy of pitch memory-an fmri study with sparse temporal sampling,"
NeuroImage, vol. 19, no. 4, p. 1417, 2003.
[17] U. Will, "Oral memory in australian song performance and the parrykirk
debate: a cognitive ethnomusicological perspective," International
Study Group on Music Archaeology, vol. X, pp. 1-29, 2004.
[18] B. Chikhaoui and H. Pigot, "Analytical model based evaluation of human
machine interfaces using cognitive modeling," International Journal of
Information Technology, vol. 4, no. 4, pp. 252-261, 2008.
[19] B. E. John and D. D. Salvucci, "Multi-purpose prototypes for assessing
user interfaces in pervasive computing systems," IEEE pervasive
computing, vol. 4, no. 4, pp. 27-34, 2005.
[20] B. Chikhaoui and H. Pigot, "Simulation of a human machine interaction:
Locate objects using a contextual assistant," in procedeengs of the 1st
International North American Simulation Technology Conference, 2008,
pp. 75-80.
[1] G. D. Sawa, "Oral transmission in arabic music, past and present," Oral
Tradition Journal, vol. 4/1-2, pp. 254-265, 1989.
[2] A. Racette and I. Peretz, "Learning lyrics: to sing or not to sing?"
Memory & Cognition Journal, vol. 35 (2), pp. 242-253, 2007.
[3] J. W. Stansell, "The use of music in learning languages: A review of the
literature," University of Illinois at Urbana-Champaign, M.Ed., 2005.
[4] M. L. Huy, "The role of music in second language learning: A vietnamese
perspective," in Conference of the Australian Association for
Research in Education and the New Zealand Association for Research
in Education, 1999.
[5] G. Mather, Foundations of Perception. Psychology Pr, 2006.
[6] C.-H. Chouard, L-oreille musicienne. Les chemins de la musique de
l-oreille au cerveau. Gallimard, 2001.
[7] J. Plantinga and L. J. Trainor, "Memory for melody: infants use a relative
pitch code," Cognition Journal, vol. 98, pp. 1-11, 2004.
[8] W. Gruhn and F. H. Rauscher, The Neurobiology of Learning: New
Approaches to Music Pedagogy Conclusions and Implications, nova ed.,
ser. Neurosciences in Music Pedagogy, 2007, ch. 10, pp. 263-295.
[9] V. J. Williamson, A. D. Baddeley, and G. J. Hitch, "Music in working
memory? examining the effect of pitch proximity on the recall
performance of nonmusicians." 9th International Conference on Music
Perception and Cognition, pp. 1581-1590, 2006.
[10] J. R. Anderson, D. Bothell, M. D. Byrne, S. Douglass, C. Lebiere, and
Y. Qin, "An integrated theory of the mind," Psychological Review, vol.
111, 136-1060, 2004.
[11] J. R. Anderson, N. A. Taatgen, and M. D. Byrne, "Learning to achieve
perfect time sharing: Architectural implications of hazeltine, teague ivry
(2002)," Journal of Experimental Psychology: Human Perception and
Performance, vol. 31, No. 4, pp. 749-761, 2005.
[12] M. D. Byrne, "Act-r/pm and menu selection: Applying a cognitive
architecture to hci," International Journal of Human-Computer Studies,
vol. 55, pp. 41-84, 2001.
[13] D. Bothell, "Act-r 6.0 reference manual," Carnegie Mellon University,
Working Draft, 2004.
[14] J. R. Anderson, D. Bothell, C. Lebiere, and M. Matessa, "An integrated
theory of list memory," Journal of Memory and Language, vol. 38, no. 4,
pp. 341-380, 1998.
[15] I. Peretz and R. Zatorre, "Brain organization for music processing,"
Annual Review of Psychology, vol. 56, pp. 89-114, 2005.
[16] N. Gaab, C. Gaser, T. Zaehle, L. Jancke, and G. Schlaug, "Functional
anatomy of pitch memory-an fmri study with sparse temporal sampling,"
NeuroImage, vol. 19, no. 4, p. 1417, 2003.
[17] U. Will, "Oral memory in australian song performance and the parrykirk
debate: a cognitive ethnomusicological perspective," International
Study Group on Music Archaeology, vol. X, pp. 1-29, 2004.
[18] B. Chikhaoui and H. Pigot, "Analytical model based evaluation of human
machine interfaces using cognitive modeling," International Journal of
Information Technology, vol. 4, no. 4, pp. 252-261, 2008.
[19] B. E. John and D. D. Salvucci, "Multi-purpose prototypes for assessing
user interfaces in pervasive computing systems," IEEE pervasive
computing, vol. 4, no. 4, pp. 27-34, 2005.
[20] B. Chikhaoui and H. Pigot, "Simulation of a human machine interaction:
Locate objects using a contextual assistant," in procedeengs of the 1st
International North American Simulation Technology Conference, 2008,
pp. 75-80.
@article{"International Journal of Information, Control and Computer Sciences:62217", author = "Belkacem Chikhaoui and Helene Pigot and Mathieu Beaudoin and Guillaume Pratte and Philippe Bellefeuille and Fernando Laudares", title = "Learning a Song: an ACT-R Model", abstract = "The 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.
", keywords = "Computational model, cognitive modeling, simulation, learning, song, music.", volume = "3", number = "7", pages = "1840-6", }
