Expressive performance in the human tenor voice

Maria Cristina Marinescu, Rafael Ramirez

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Resumen

This paper presents preliminary results on expressive performance in the human tenor voice. This work investigates how professional opera singers manipulate sound properties such as timing, amplitude, and pitch in order to produce expressive performances. We also consider the contribution of features of prosody in the artistic delivery of an operatic aria. Our approach is based on applying machine learning to extract patterns of expressive singing from performances by Josep Carreras. This is a step towards recognizing performers by their singing style, capturing some of the aspects which make two performances of the same piece sound different, and understanding whether there exists a correlation between the occurrences correctly covered by a pattern and specific emotional attributes.

Idioma originalInglés
Título de la publicación alojadaProceedings of the 5th Sound and Music Computing Conference, SMC 2008
EditorialSound and music Computing network
ISBN (versión impresa)9783798320949
EstadoPublicada - 2008
Publicado de forma externa
Evento5th Sound and Music Computing Conference, SMC 2008 - Berlin, Alemania
Duración: 31 jul 20083 ago 2008

Serie de la publicación

NombreProceedings of the 5th Sound and Music Computing Conference, SMC 2008

Conferencia

Conferencia5th Sound and Music Computing Conference, SMC 2008
País/TerritorioAlemania
CiudadBerlin
Período31/07/083/08/08

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