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Abstract:

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.

Registro:

Documento: Artículo
Título:A composition algorithm based on crossmodal taste-music correspondences
Autor:Mesz, B.; Sigman, M.; Trevisan, M.
Filiación:Laboratory of Musical Research and Production (LIPM), Centro Cultural Recoleta, Junín 1930, C1113AAX, Buenos Aires, Argentina
Laboratory of Integrative Neuroscience, Physics dept., FCEN, University of Buenos Aires. Ciudad Universitaria, 1428EGA, Buenos Aires, Argentina
Laboratory of Dynamical Systems, IFIBA-Physics dept., FCEN, University of Buenos Aires. Ciudad Universitaria, 1428EGA, Buenos Aires, Argentina
Palabras clave: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
Año:2012
Número:MARCH 2012
DOI: http://dx.doi.org/10.3389/fnhum.2012.00071
Título revista:Frontiers in Human Neuroscience
Título revista abreviado:Front. Human Neurosci.
ISSN:16625161
PDF:https://bibliotecadigital.exactas.uba.ar/download/paper/paper_16625161_v_nMARCH2012_p_Mesz.pdf
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_16625161_v_nMARCH2012_p_Mesz

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Citas:

---------- APA ----------
Mesz, B., Sigman, M. & Trevisan, M. (2012) . A composition algorithm based on crossmodal taste-music correspondences. Frontiers in Human Neuroscience(MARCH 2012).
http://dx.doi.org/10.3389/fnhum.2012.00071
---------- CHICAGO ----------
Mesz, B., Sigman, M., Trevisan, M. "A composition algorithm based on crossmodal taste-music correspondences" . Frontiers in Human Neuroscience, no. MARCH 2012 (2012).
http://dx.doi.org/10.3389/fnhum.2012.00071
---------- MLA ----------
Mesz, B., Sigman, M., Trevisan, M. "A composition algorithm based on crossmodal taste-music correspondences" . Frontiers in Human Neuroscience, no. MARCH 2012, 2012.
http://dx.doi.org/10.3389/fnhum.2012.00071
---------- VANCOUVER ----------
Mesz, B., Sigman, M., Trevisan, M. A composition algorithm based on crossmodal taste-music correspondences. Front. Human Neurosci. 2012(MARCH 2012).
http://dx.doi.org/10.3389/fnhum.2012.00071