Using Probabilistic Parsers to Support Salsa Music Composition

Brayan Rodríguez, Raúl Gutiérrez De Piñérez, Gerardo M. Sarria

Producción: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

Salsa is a long-established music genre. It has been used as a way to define, identify and express social beliefs. Due to the limited computational study of this genre, we consider relevant to identify and analyze the musical features of this music genre. Thus, we train a corpus with Grupo Niche songs for generating the production rules for an induced probabilistic context-free grammar through a probabilistic parser. In addition, we implement a web-based tool to support musical composition and generate automatic Salsa songs. In this work, we also compare three automatic songs using cross-validation on the corpus. We show the stability of the grammar because the precision of the generated songs compared to corpus’ songs is close to those that are not in the corpus.

Idioma originalInglés
Título de la publicación alojadaMathematics and Computation in Music - 6th International Conference, MCM 2017, Proceedings
EditoresOctavio A. Agustin-Aquino, Emilio Lluis-Puebla, Mariana Montiel
EditorialSpringer Verlag
Páginas361-372
Número de páginas12
ISBN (versión impresa)9783319718262
DOI
EstadoPublicada - 2017
Evento6th International Conference on Mathematics and Computation in Music, MCM 2017 - Mexico City, México
Duración: 26 jun. 201729 jun. 2017

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen10527 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia6th International Conference on Mathematics and Computation in Music, MCM 2017
País/TerritorioMéxico
CiudadMexico City
Período26/06/1729/06/17

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