Name
Abstract | ||
|---|---|---|
Several approaches based on the 'Markov chain model' have been proposed to tackle the composer identification task. In the paper at hand, we propose to capture phrasing structural information from inter onset and pitch intervals of pairs of consecutive notes in a musical piece, by incorporating this information into a weighted variation of a first order Markov chain model. Additionally, we propose an evolutionary procedure that automatically tunes the introduced weights and exploits the full potential of the proposed model for tackling the composer identification task between two composers. Initial experimental results on string quartets of Haydn, Mozart and Beethoven suggest that the proposed model performs well and can provide insights on the inter onset and pitch intervals on the considered musical collection. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1007/978-3-642-20520-0_34 | EvoApplications (2) |
Keywords | Field | DocType |
pitch interval,weighted markov chain model,phrasing structural information,markov chain model,order markov chain model,musical piece,musical collection,composer identification task,consecutive note,inter onset,musical composer identification,first order | Music information retrieval,Musical,First order,Markov model,Computer science,Markov chain,Differential evolution,Speech recognition,Artificial intelligence,MOZART | Conference |
Volume | ISSN | Citations |
6625 | 0302-9743 | 5 |
PageRank | References | Authors |
0.74 | 12 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maximos A. Kaliakatsos-Papakostas | 1 | 67 | 13.26 |
| Michael G. Epitropakis | 2 | 93 | 8.39 |
| M.N. Vrahatis | 3 | 1740 | 151.65 |