Perceptive%20Strategies%20in%20Computational%20Motivic%20Analysis:%20Why%20and%20How.

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Perceptive Strategiesin Computational Motivic
AnalysisWhy and How.

• Olivier.Lartillot_at_ircam.fr
• www.ircam.fr/equipes/repmus/lartillot

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Perceptive Strategiesin Computational Motivic
AnalysisWhy 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.

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Perceptive Strategiesin Computational Motivic
AnalysisWhy and How.

• Olivier.Lartillot_at_ircam.fr
• www.ircam.fr/equipes/repmus/lartillot

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Computational Motivic Analysis

• Automated Music Analysis
• Motivic Analysis
• Rudolph Reti
• Nicolas Ruwet Paradigmatic Analysis
• Musical Pattern Discovery
• Exact Pattern
• Dynamic Programming

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Dynamic Programming
ACGGCGTTACGGCAGCGCTGATCGTATCTAGCTAGTCTATGCTAT
ACGGCGTTACGAGCAGCGCTGATCGTATCTAGTAGTCTATGCGAT
CDEFGFEADGAGFEF?
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Automated Music Analysis

• Motivic Analysis
• Rudolph Reti
• Nicolas Ruwet Paradigmatic Analysis
• Musical Pattern Discovery
• Exact Pattern
• Dynamic Programming
• Perceptual Model?

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Music Semiology
Immanent Structures?
Score
Composer
Listener
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Immanent Structures?
Bad patterns
Good patterns
Transcendent Structures!
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Automated Music Analysis

• Motivic Analysis
• Rudolph Reti
• Nicolas Ruwet Paradigmatic Analysis
• Musical Pattern Discovery
• Exact Pattern
• Dynamic Programming
• Perceptual Model

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Perceptive Strategiesin Computational Motivic
AnalysisWhy and How.

• Olivier.Lartillot_at_ircam.fr
• www.ircam.fr/equipes/repmus/lartillot

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Temporal Approach
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Temporal Approach
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Apprehensive Retention
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Apprehensive Retention
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Reproductive Remembering
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Objectivation
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Recognitive Remembering
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Recognitive Remembering
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Pattern Repetition
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Abstract Pattern
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Abstract Pattern Tree
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Pattern Occurrence Chain
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Parallel Patterns
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Architecture

• loop for note in score
• memorize new retentions
• develop current expected occurrences
• develop current unexpected occurrences
• develop current objectivations
• find new objectivations

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OMkanthus 0.1