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Título:
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Melodic pattern extraction in large collections of music recordings using time series mining techniques
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Autor/a:
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Gulati, Sankalp; Serrà Julià, Joan; Ishwar, Vignesh; Serra, Xavier
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Abstract:
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Comunicació presentada a la 15th International Society for Music Information Retrieval Conference (ISMIR 2014), celebrada els dies 27 a 31 d'octubre de 2014 a Taipei, Taiwan. |
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Abstract:
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We demonstrate a data-driven unsupervised approach for
the discovery of melodic patterns in large collections of
Indian art music recordings. The approach first works on
single recordings and subsequently searches in the entire
music collection. Melodic similarity is based on dynamic
time warping. The task being computationally intensive,
lower bounding and early abandoning techniques are applied
during distance computation. Our dataset comprises
365 hours of music, containing 1,764 audio recordings representing
the melodic diversity of Carnatic music. A preliminary
evaluation based on expert feedback on a subset
of the music collection shows encouraging results. In particular,
several musically interesting relationships are discovered,
yielding further scope for establishing novel similarity
measures based on melodic patterns. |
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Materia(s):
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-Carnatic music
-Indian art music
-Melodic analysis
-Melodic patterns
-Motifs |
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Derechos:
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© Sankalp Gulati, Joan Serrà, Vignesh Ishwar, Xavier
Serra. Licensed under a Creative Commons Attribution 4.0 International
License (CC BY 4.0). Attribution: Sankalp Gulati, Joan Serrà, Vignesh
Ishwar, Xavier Serra. “Melodic Pattern Extraction in Large Collections
of Music Recordings Using Time Series Mining Techniques”, 15th International
Society for Music Information Retrieval Conference, 2014.
https://creativecommons.org/licenses/by/4.0/
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Tipo de documento:
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Objeto de conferencia
Artículo - Versión publicada |
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Editor:
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International Society for Music Information Retrieval (ISMIR)
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Compartir:
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