Change search
ReferencesLink to record
Permanent link

Direct link
Articulation strategies in expressive piano performance - Analysis of legato, staccato, and repeated notes in performances of the Andante movement of Mozart's Sonata in G major (K 545)
KTH, Superseded Departments, Speech, Music and Hearing.ORCID iD: 0000-0002-3086-0322
2000 (English)In: Journal of New Music Research, ISSN 0929-8215, Vol. 29, no 3, 211-224 p.Article in journal (Refereed) Published
Abstract [en]

Articulation strategies applied by pianists in expressive performances of the same core are analysed. Measurements of key overlap time and its relation to the inter-onset-interval are collected for notes marked legato and staccato in the first sixteen bars of the Andante movement of W.A. Mozart's Piano Sonata in G major, K 545. Five pianists played the piece nine times. First, they played in a wa that they considered "optimal". In the remaining eight performances they were asked to represent different expressive characters, as specified in terms of different adjectives. Legato,staccato, and repeated notes articulation applied by the right hand were examined by means of statistical analysis. Although the results varied considerably between pianists, some trends could be observed. The pianists generally used similar strategies in the rendering intended to represent different expressive characters. legato was played with a key overlap ratio that depended on the inter-onset-interval (IOI). Staccato tones had approximate duration of 40% of the IOI. Repeated notes were played with a duration of about 60% of the IOI. The results seem useful as a basis for articulation rules in grammars for automatic piano performance.

Place, publisher, year, edition, pages
2000. Vol. 29, no 3, 211-224 p.
Keyword [en]
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-12921DOI: 10.1076/jnmr. 000168323100004OAI: diva2:319627
QC 20100519Available from: 2010-05-19 Created: 2010-05-19 Last updated: 2012-06-13Bibliographically approved
In thesis
1. Virtual virtuosity
Open this publication in new window or tab >>Virtual virtuosity
2000 (English)Doctoral thesis, comprehensive summary (Other scientific)
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.

Place, publisher, year, edition, pages
Stockholm: KTH, 2000. ix, 32 p.
Trita-TMH, 2000:9
music, performance, expression, interpretation, piano, automatic, artificial neural networks
National Category
Engineering and Technology
urn:nbn:se:kth:diva-3049 (URN)91-7170-643-7 (ISBN)
Public defence
2000-12-01, 00:00 (English)
QC 20100518Available from: 2000-11-29 Created: 2000-11-29 Last updated: 2010-05-19Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Bresin, Roberto
By organisation
Speech, Music and Hearing
In the same journal
Journal of New Music Research
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 106 hits
ReferencesLink to record
Permanent link

Direct link