Autores
Rangel Nahum Carlos Alexis
Godoy Calderón Salvador
Calvo Castro Francisco Hiram
Título Deep symbolic processing of human-performed musical sequences
Tipo Revista
Sub-tipo JCR
Descripción Journal of Intelligent & Fuzzy Systems
Resumen Artificial music tutors are needed for assisting a performer during his/her practice time whenever a human tutor is not available. But for these artificial tutors to be intelligent and fulfill the role of a music tutor, they have to be able to identify errors made by the performer while playing a musical sequence. This task is not a trivial one, since all musical activities are considered as open-ended domains. Therefore, not only there is no unique correct way of performing a musical sequence, but also the analysis made by the tutor has to consider the development level of the performer, the difficulty level of the performed musical sequence, and many other variables. This paper describes an ongoing research that uses cascading connected layers of symbolic processing as the core of a human-performed error identification and characterization module able to overcome the complexity of the studied open-ended domain. © 2022 - IOS Press. All rights reserved.
Observaciones DOI 10.3233/JIFS-219261
Lugar Amsterdam
País Paises Bajos
No. de páginas 4739-4750
Vol. / Cap. v. 42 no. 5
Inicio 2022-03-31
Fin
ISBN/ISSN