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This is the official Website of the Society for Mathematics and Computation in Music (SMCM).
The Society was founded in 2006 as an International Forum for researchers and musicians working in the trans-disciplinary field at the intersection of music, mathematics and computation.
Home Newsletters Registration ContactWelcome!This is the official Website of the Society for Mathematics and Computation in Music (SMCM).The Society was founded in 2006 as an International Forum for researchers and musicians working in the trans-disciplinary field at the intersection of music, mathematics and computation.
In this research, it is proposed that music can be thought of as random processes, and music style recognition can be thought of as a system identification problem. Then, a general framework for modeling music using Markov chains is described, and based on this framework, a two-way composer identification scheme is demonstrated. The scheme utilizes the Kullback-Leibler distance as the metric between distribution functions, and it is shown that under the condition when the marginals are identical, the scheme gives maximum likelihood identification. Experiments of composer identification are conducted on all the string quartets written by Mozart and Haydn, and the results are documented and discussed.
In this research, it is proposed that music can be thought of as random processes, and music style recognition can be thought of as a system identification problem. Then, a general framework for modeling music using Markov chains is described, and based on this framework, a two-way composer identification scheme is demonstrated. The scheme utilizes the Kullback-Leibler distance as the metric between distribution functions, and it is shown that under the condition when the marginals are identical, the scheme gives maximum likelihood identification. Experiments of composer identification are conducted on all the string quartets written by Mozart and Haydn, and the results are documented and discussed.