A composition algorithm based on cross modal 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.A.
Formato: JOUR
Materias:
Cross-modal associations
Music
Musical algorithm
Semantics
Taste
adult
algorithm
article
auditory discrimination
auditory memory
auditory response
female
human
human experiment
language ability
male
Monte Carlo method
music
semantics
sensory analysis
sensory feedback
sound analysis
stimulus response
task performance
taste discrimination
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_16625161_v_nAPRIL2012_p_Mesz
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_16625161_v_nAPRIL2012_p_Mesz
record_format dspace
spelling todo:paper_16625161_v_nAPRIL2012_p_Mesz2023-10-03T16:28:53Z A composition algorithm based on cross modal taste-music correspondences Mesz, B. Sigman, M. Trevisan, M.A. Cross-modal associations Music Musical algorithm Semantics Taste adult algorithm article auditory discrimination auditory memory auditory response female human human experiment language ability male Monte Carlo method music semantics sensory analysis sensory feedback sound analysis stimulus response 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 (Mesz et al., 2011). 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.A. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_16625161_v_nAPRIL2012_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)
topic Cross-modal associations
Music
Musical algorithm
Semantics
Taste
adult
algorithm
article
auditory discrimination
auditory memory
auditory response
female
human
human experiment
language ability
male
Monte Carlo method
music
semantics
sensory analysis
sensory feedback
sound analysis
stimulus response
task performance
taste discrimination
spellingShingle Cross-modal associations
Music
Musical algorithm
Semantics
Taste
adult
algorithm
article
auditory discrimination
auditory memory
auditory response
female
human
human experiment
language ability
male
Monte Carlo method
music
semantics
sensory analysis
sensory feedback
sound analysis
stimulus response
task performance
taste discrimination
Mesz, B.
Sigman, M.
Trevisan, M.A.
A composition algorithm based on cross modal taste-music correspondences
topic_facet Cross-modal associations
Music
Musical algorithm
Semantics
Taste
adult
algorithm
article
auditory discrimination
auditory memory
auditory response
female
human
human experiment
language ability
male
Monte Carlo method
music
semantics
sensory analysis
sensory feedback
sound analysis
stimulus response
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 (Mesz et al., 2011). 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 JOUR
author Mesz, B.
Sigman, M.
Trevisan, M.A.
author_facet Mesz, B.
Sigman, M.
Trevisan, M.A.
author_sort Mesz, B.
title A composition algorithm based on cross modal taste-music correspondences
title_short A composition algorithm based on cross modal taste-music correspondences
title_full A composition algorithm based on cross modal taste-music correspondences
title_fullStr A composition algorithm based on cross modal taste-music correspondences
title_full_unstemmed A composition algorithm based on cross modal taste-music correspondences
title_sort composition algorithm based on cross modal taste-music correspondences
url http://hdl.handle.net/20.500.12110/paper_16625161_v_nAPRIL2012_p_Mesz
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AT meszb compositionalgorithmbasedoncrossmodaltastemusiccorrespondences
AT sigmanm compositionalgorithmbasedoncrossmodaltastemusiccorrespondences
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