A composition algorithm based on crossmodal taste-music correspondences

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While there is broad consensus about the structural similarities between language and music, comparably less attention has been devoted to semantic correspondences between these two ubiquitous manifestations of human culture. We have investigated the relations between music and a narrow and bounded...

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Detalles Bibliográficos
Autores principales: Mesz, B., Sigman, M., Trevisan, M.
Formato: Artículo publishedVersion
Lenguaje:Inglés
Publicado: 2012
Materias:
Algorithm
Composition
Cross-modal
Language
Music
Semantics
Taste
adult
article
association
auditory discrimination
auditory feedback
auditory stimulation
bitter taste
controlled study
female
gesture
human
human experiment
language processing
learning algorithm
male
music
normal human
process development
scoring system
semantics
stimulus response
sweetness
task performance
taste discrimination
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_16625161_v_nMARCH2012_p_Mesz
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id paperaa:paper_16625161_v_nMARCH2012_p_Mesz
record_format dspace
spelling paperaa:paper_16625161_v_nMARCH2012_p_Mesz2023-06-12T16:50:52Z A composition algorithm based on crossmodal taste-music correspondences Front. Human Neurosci. 2012(MARCH 2012) Mesz, B. Sigman, M. Trevisan, M. Algorithm Composition Cross-modal Language Music Semantics Taste adult article association auditory discrimination auditory feedback auditory stimulation bitter taste controlled study female gesture human human experiment language processing learning algorithm male music normal human process development scoring system semantics stimulus response sweetness task performance taste discrimination While there is broad consensus about the structural similarities between language and music, comparably less attention has been devoted to semantic correspondences between these two ubiquitous manifestations of human culture. We have investigated the relations between music and a narrow and bounded domain of semantics: the words and concepts referring to taste sensations. In a recent work, we found that taste words were consistently mapped to musical parameters. Bitter is associated with low-pitched and continuous music (legato), salty is characterized by silences between notes (staccato), sour is high pitched, dissonant and fast and sweet is consonant, slow and soft (Mesz2011). Here we extended these ideas, in a synergistic dialog between music and science, investigating whether music can be algorithmically generated from taste-words. We developed and implemented an algorithm that exploits a large corpus of classic and popular songs. New musical pieces were produced by choosing fragments from the corpus and modifying them to minimize their distance to the region in musical space that characterizes each taste. In order to test the capability of the produced music to elicit significant associations with the different tastes, musical pieces were produced and judged by a group of non musicians. Results showed that participants could decode well above chance the taste-word of the composition. We also discuss how our findings can be expressed in a performance bridging music and cognitive science. © 2012 Mesz, Sigman and Trevisan. Fil:Mesz, B. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Sigman, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Trevisan, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. 2012 info:eu-repo/semantics/article info:ar-repo/semantics/artículo info:eu-repo/semantics/publishedVersion application/pdf eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_16625161_v_nMARCH2012_p_Mesz
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
language Inglés
orig_language_str_mv eng
topic Algorithm
Composition
Cross-modal
Language
Music
Semantics
Taste
adult
article
association
auditory discrimination
auditory feedback
auditory stimulation
bitter taste
controlled study
female
gesture
human
human experiment
language processing
learning algorithm
male
music
normal human
process development
scoring system
semantics
stimulus response
sweetness
task performance
taste discrimination
spellingShingle Algorithm
Composition
Cross-modal
Language
Music
Semantics
Taste
adult
article
association
auditory discrimination
auditory feedback
auditory stimulation
bitter taste
controlled study
female
gesture
human
human experiment
language processing
learning algorithm
male
music
normal human
process development
scoring system
semantics
stimulus response
sweetness
task performance
taste discrimination
Mesz, B.
Sigman, M.
Trevisan, M.
A composition algorithm based on crossmodal taste-music correspondences
topic_facet Algorithm
Composition
Cross-modal
Language
Music
Semantics
Taste
adult
article
association
auditory discrimination
auditory feedback
auditory stimulation
bitter taste
controlled study
female
gesture
human
human experiment
language processing
learning algorithm
male
music
normal human
process development
scoring system
semantics
stimulus response
sweetness
task performance
taste discrimination
description While there is broad consensus about the structural similarities between language and music, comparably less attention has been devoted to semantic correspondences between these two ubiquitous manifestations of human culture. We have investigated the relations between music and a narrow and bounded domain of semantics: the words and concepts referring to taste sensations. In a recent work, we found that taste words were consistently mapped to musical parameters. Bitter is associated with low-pitched and continuous music (legato), salty is characterized by silences between notes (staccato), sour is high pitched, dissonant and fast and sweet is consonant, slow and soft (Mesz2011). Here we extended these ideas, in a synergistic dialog between music and science, investigating whether music can be algorithmically generated from taste-words. We developed and implemented an algorithm that exploits a large corpus of classic and popular songs. New musical pieces were produced by choosing fragments from the corpus and modifying them to minimize their distance to the region in musical space that characterizes each taste. In order to test the capability of the produced music to elicit significant associations with the different tastes, musical pieces were produced and judged by a group of non musicians. Results showed that participants could decode well above chance the taste-word of the composition. We also discuss how our findings can be expressed in a performance bridging music and cognitive science. © 2012 Mesz, Sigman and Trevisan.
format Artículo
Artículo
publishedVersion
author Mesz, B.
Sigman, M.
Trevisan, M.
author_facet Mesz, B.
Sigman, M.
Trevisan, M.
author_sort Mesz, B.
title A composition algorithm based on crossmodal taste-music correspondences
title_short A composition algorithm based on crossmodal taste-music correspondences
title_full A composition algorithm based on crossmodal taste-music correspondences
title_fullStr A composition algorithm based on crossmodal taste-music correspondences
title_full_unstemmed A composition algorithm based on crossmodal taste-music correspondences
title_sort composition algorithm based on crossmodal taste-music correspondences
publishDate 2012
url http://hdl.handle.net/20.500.12110/paper_16625161_v_nMARCH2012_p_Mesz
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