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PRAIg '16 / +pics


AERFAI Summer School on Deep Learning


Alicante July 5-6, 2017

10th international workshop on Machine Learning and Music


Barcelona: 16th October 2017



  1. Pérez-Sancho, C.
    "Stochastic Language Models for Music Information Retrieval"
    PhD Thesis. Supervisors: José M. Iñesta, Jorge Calera Rubio
    Universidad de Alicante, Alicante, Spain (2009)
    : bibtex : pdf

    Music Information Retrieval (MIR) is an interdisciplinary research area that aims at providing solutions to most problems related to the access to multimedia databases, in particular those with musical content, either in symbolic (MIDI) or audio format. An especially relevant problem is the automatic organization and indexation of data, since carrying out these tasks by hand would require an overwhelming effort for most people and institutions. One of the most relevant features that can be obtained from a song in order to perform its automatic organization is the musical style, since it is one of the most popular fields used by people when accessing musical databases and catalogs. In this thesis it has been studied to what extent the musical style of a piece can be determined using just the information contained in its score, by applying pattern recognition techniques on melodic and harmonic sequences obtained from musical scores.

@phdthesis {
 author = "Pérez-Sancho, C.",
 title  = "Stochastic Language Models for Music Information Retrieval",
 address = "Alicante, Spain",
 editor = "José M. Iñesta, Jorge Calera Rubio",
 month = "July",
 organization = "Universidad de Alicante",
 year = "2009"
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