Style recognition through statistical event models
Carlos Pérez-Sancho, José Iñesta and Jorge Calera-Rubio
Journal of new Music Research
The automatic classification of music fragments into styles is one
challenging problem within the music information retrieval (MIR) domain and
also for the understanding of music style perception. This has a number of
applications, including the indexation and exploration of musical databases.
Some technologies employed in text classification can be applied to this
problem. The key point here is to establish the music equivalent to the
words in texts. A number of works use the combination of intervals and
duration ratios for this purpose. In this paper, different statistical text
recognition algorithms are applied to style recognition using this kind of
melody representation, exploring their performance for different word sizes.
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