A composition algorithm based on crossmodal taste-music correspondences

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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Autor principal: Mesz, B.
Otros Autores: Sigman, M., Trevisan, M.
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: 2012
Acceso en línea:Registro en Scopus
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100 1 |a Mesz, B. 
245 1 2 |a A composition algorithm based on crossmodal taste-music correspondences 
260 |c 2012 
270 1 0 |m Trevisan, M.; Laboratorio de Sistemas Dinámicos, Departamento de Física-IFIBA, Pabellón I, Ciudad Universitaria, 1428EGA, Buenos Aires, Argentina; email: marcos@df.uba.ar 
506 |2 openaire  |e Política editorial 
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504 |a Mesz, B., Trevisan, M.A., Sigman, M., The taste of music (2011) Perception, 40, pp. 209-219 
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520 3 |a 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.  |l eng 
593 |a Laboratory of Musical Research and Production (LIPM), Centro Cultural Recoleta, Junín 1930, C1113AAX, Buenos Aires, Argentina 
593 |a Laboratory of Integrative Neuroscience, Physics dept., FCEN, University of Buenos Aires. Ciudad Universitaria, 1428EGA, Buenos Aires, Argentina 
593 |a Laboratory of Dynamical Systems, IFIBA-Physics dept., FCEN, University of Buenos Aires. Ciudad Universitaria, 1428EGA, Buenos Aires, Argentina 
690 1 0 |a ALGORITHM 
690 1 0 |a COMPOSITION 
690 1 0 |a CROSS-MODAL 
690 1 0 |a LANGUAGE 
690 1 0 |a MUSIC 
690 1 0 |a SEMANTICS 
690 1 0 |a TASTE 
690 1 0 |a ADULT 
690 1 0 |a ARTICLE 
690 1 0 |a ASSOCIATION 
690 1 0 |a AUDITORY DISCRIMINATION 
690 1 0 |a AUDITORY FEEDBACK 
690 1 0 |a AUDITORY STIMULATION 
690 1 0 |a BITTER TASTE 
690 1 0 |a CONTROLLED STUDY 
690 1 0 |a FEMALE 
690 1 0 |a GESTURE 
690 1 0 |a HUMAN 
690 1 0 |a HUMAN EXPERIMENT 
690 1 0 |a LANGUAGE PROCESSING 
690 1 0 |a LEARNING ALGORITHM 
690 1 0 |a MALE 
690 1 0 |a MUSIC 
690 1 0 |a NORMAL HUMAN 
690 1 0 |a PROCESS DEVELOPMENT 
690 1 0 |a SCORING SYSTEM 
690 1 0 |a SEMANTICS 
690 1 0 |a STIMULUS RESPONSE 
690 1 0 |a SWEETNESS 
690 1 0 |a TASK PERFORMANCE 
690 1 0 |a TASTE DISCRIMINATION 
700 1 |a Sigman, M. 
700 1 |a Trevisan, M. 
773 0 |d 2012  |k n. MARCH 2012  |p Front. Human Neurosci.  |x 16625161  |w (AR-BaUEN)CENRE-7999  |t Frontiers in Human Neuroscience 
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