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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 (Engelska)Ingår i: Proceedings of the InternationalComputer Music Conference 2000 / [ed] Zannos, Ioannis, San Francisco, USA: Computer Music Association , 2000, s. 499-502Konferensbidrag, Publicerat paper (Refereegranskat)
Ort, förlag, år, upplaga, sidor
San Francisco, USA: Computer Music Association , 2000. s. 499-502
Nationell ämneskategori
Data- och informationsvetenskap
Forskningsämne
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
Konferens
International Computer Music Conference
Anmärkning

QC 20100519

Tillgänglig från: 2010-05-19 Skapad: 2010-05-19 Senast uppdaterad: 2018-09-13Bibliografiskt granskad
Ingår i avhandling
1. Virtual virtuosity
Öppna denna publikation i ny flik eller fönster >>Virtual virtuosity
2000 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
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.

Ort, förlag, år, upplaga, sidor
Stockholm: KTH, 2000. s. ix, 32
Serie
Trita-TMH ; 2000:9
Nyckelord
music, performance, expression, interpretation, piano, automatic, artificial neural networks
Nationell ämneskategori
Teknik och teknologier
Identifikatorer
urn:nbn:se:kth:diva-3049 (URN)91-7170-643-7 (ISBN)
Disputation
2000-12-01, 00:00 (Engelska)
Anmärkning
QC 20100518Tillgänglig från: 2000-11-29 Skapad: 2000-11-29 Senast uppdaterad: 2010-05-19Bibliografiskt granskad

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