Transcript Perceptive Strategies in Computational Motivic Analysis.

Perceptive Strategies
in Computational Motivic Analysis:
Why and How.
[email protected]
www.ircam.fr/equipes/repmus/lartillot
Perceptive Strategies
in Computational Motivic Analysis:
Why and How.
The motivic dimension of music, still resisting to a complete and thorough explication, remains one of
the most ambitious domains of interest of music analysis. Music semiology has inspired an ideal of
“neutrality”, of the possibility of total independence of the structure to perceptual context. This
paradigm has been questioned by competing tendencies that defend the need of a perceptual or even
“cognitive” foundation of music analysis. Such dilemma finds a new resonance in today research in
automatic musical pattern discovery, which may be considered as a computational inquiry of motivic
analysis. Current limitations in this domain seem to stem from an insufficient consideration of the
perceptual specificity of musical expression. We propose a general computational model that
attempts to mimic music perception. This model relies on two main temporal characteristics of
music: chronological direction and short-term selectivity. As a result, musical pattern is defined as an
aggregation of successive local intervals. Patterns are induced by analogy between current context
and similar past contexts that are reactivated through associative memory. Here, patterns are
conceived of as concepts that are actualized in the musical score. This score is represented as a
network of notes, which are linked to pattern occurrences that themselves form meta-patterns of
patterns. This computational modelling, in process of development as an Open Music library called
OMkanthus, aims at offering to musicology a detailed and explicit understanding of music,
and suggesting to cognitive science the necessary conditions for musical pattern perception.
Perceptive Strategies
in Computational Motivic Analysis:
Why and How.
[email protected]
www.ircam.fr/equipes/repmus/lartillot
Computational Motivic Analysis
• Automated Music Analysis
• Motivic Analysis
– Rudolph Reti
– Nicolas Ruwet: Paradigmatic Analysis
• Musical Pattern Discovery
– Exact Pattern
– Dynamic Programming
Dynamic Programming
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ACGGCGTTACGAGCAGCGCTGATCGTATCTAGTAGTCTATGCGAT
CDEFGFEADGAGFEF?
Automated Music Analysis
• Motivic Analysis
– Rudolph Reti
– Nicolas Ruwet: Paradigmatic Analysis
• Musical Pattern Discovery
– Exact Pattern
– Dynamic Programming
Perceptual Model?
Music Semiology
Cognitive Constraints
Cultural Knowledge
Immanent Structures?
Composer
Poietic Level
Score
Neutral Level
Listener
Esthesic Level
Immanent Structures?
Bad patterns
Good patterns
Transcendent Structures!
Automated Music Analysis
• Motivic Analysis
– Rudolph Reti
– Nicolas Ruwet: Paradigmatic Analysis
• Musical Pattern Discovery
– Exact Pattern
– Dynamic Programming
Perceptual Model
Perceptive Strategies
in Computational Motivic Analysis:
Why and How.
[email protected]
www.ircam.fr/equipes/repmus/lartillot
Temporal Approach
Temporal Approach
Apprehensive Retention
Apprehensive Retention
Reproductive Remembering
Objectivation
Recognitive Remembering
Recognitive Remembering
Pattern Repetition
Abstract Pattern
Abstract Pattern Tree
Pattern Occurrence Chain
Parallel Patterns
Architecture
• loop for note in score
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memorize new retentions
develop current expected occurrences
develop current unexpected occurrences
develop current objectivations
find new objectivations
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OMkanthus 0.1