Score Analyzer: Extracting performance information for instrumental e-learning
Résumé
Today, most musical scores can be downloaded on the Web, often for free. However, beginners can have difficulties in finding a score appropriate to their level, and should often rely on themselves to start out on the chosen piece. In this instrumental e-Learning context, we propose a Score Analyzer service in order to automatically extract difficult parts within a MusicXML piece and suggest advice thanks to a Musical Sign Base (MSB). To do so, we first study how teachers introduce a piece to their students and propose a corresponding descriptive logic. We then identify seven criteria to characterize technical instrumental difficulties and propose methods to extract them from a MusicXML score. These criteria are implemented in a Score Analyzer prototype. Its first results are confronted to pianists' estimations. Finally we discuss the integration of this work to @-MUSE, a collaborative score annotation platform based on multimedia contents indexation.
Mots clés
@-MUSE
@nnotation platform for musical education
collaborative platform
collaborative score annotation platform
computer aided instruction
decision support
Estimation
information retrieval
instrumental e-learning
Instruments
Internet
MSB
multimedia content indexation
music
musical instruments
musical score
musical sign base
MusicXML score
Ontologies
performance information extraction
pianist estimation
Prototypes
score analyzer prototype
sign management
teachers
teaching
technical instrumental difficulties
Thumb
Web
XML