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Software tools for musical expression.
KTH, Tidigare Institutioner (före 2005), Tal, musik och hörsel.ORCID-id: 0000-0002-3086-0322
KTH, Tidigare Institutioner (före 2005), Tal, musik och hörsel.ORCID-id: 0000-0003-2926-6518
2000 (engelsk)Inngår i: Proceedings of the InternationalComputer Music Conference 2000 / [ed] Zannos, Ioannis, San Francisco, USA: Computer Music Association , 2000, s. 499-502Konferansepaper, Publicerat paper (Fagfellevurdert)
sted, utgiver, år, opplag, sider
San Francisco, USA: Computer Music Association , 2000. s. 499-502
HSV kategori
Forskningsprogram
Tal- och musikkommunikation
Identifikatorer
URN: urn:nbn:se:kth:diva-12924ISBN: 0-9667927-2-6 (tryckt)OAI: oai:DiVA.org:kth-12924DiVA, id: diva2:319631
Konferanse
International Computer Music Conference
Merknad

QC 20100519

Tilgjengelig fra: 2010-05-19 Laget: 2010-05-19 Sist oppdatert: 2018-09-13bibliografisk kontrollert
Inngår i avhandling
1. Virtual virtuosity
Åpne denne publikasjonen i ny fane eller vindu >>Virtual virtuosity
2000 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

This dissertation presents research in the field ofautomatic music performance with a special focus on piano.

A system is proposed for automatic music performance, basedon artificial neural networks (ANNs). A complex,ecological-predictive ANN was designed thatlistensto the last played note,predictsthe performance of the next note,looksthree notes ahead in the score, and plays thecurrent tone. This system was able to learn a professionalpianist's performance style at the structural micro-level. In alistening test, performances by the ANN were judged clearlybetter than deadpan performances and slightly better thanperformances obtained with generative rules.

The behavior of an ANN was compared with that of a symbolicrule system with respect to musical punctuation at themicro-level. The rule system mostly gave better results, butsome segmentation principles of an expert musician were onlygeneralized by the ANN.

Measurements of professional pianists' performances revealedinteresting properties in the articulation of notes markedstaccatoandlegatoin the score. Performances were recorded on agrand piano connected to a computer.Staccatowas realized by a micropause of about 60% ofthe inter-onset-interval (IOI) whilelegatowas realized by keeping two keys depressedsimultaneously; the relative key overlap time was dependent ofIOI: the larger the IOI, the shorter the relative overlap. Themagnitudes of these effects changed with the pianists' coloringof their performances and with the pitch contour. Theseregularities were modeled in a set of rules for articulation inautomatic piano music performance.

Emotional coloring of performances was realized by means ofmacro-rules implemented in the Director Musices performancesystem. These macro-rules are groups of rules that werecombined such that they reflected previous observations onmusical expression of specific emotions. Six emotions weresimulated. A listening test revealed that listeners were ableto recognize the intended emotional colorings.

In addition, some possible future applications are discussedin the fields of automatic music performance, music education,automatic music analysis, virtual reality and soundsynthesis.

sted, utgiver, år, opplag, sider
Stockholm: KTH, 2000. s. ix, 32
Serie
Trita-TMH ; 2000:9
Emneord
music, performance, expression, interpretation, piano, automatic, artificial neural networks
HSV kategori
Identifikatorer
urn:nbn:se:kth:diva-3049 (URN)91-7170-643-7 (ISBN)
Disputas
2000-12-01, 00:00 (engelsk)
Merknad
QC 20100518Tilgjengelig fra: 2000-11-29 Laget: 2000-11-29 Sist oppdatert: 2010-05-19bibliografisk kontrollert

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