perceptive strategies in computational motivic analysis: why and how

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Perceptive Strategies in Computational Motivic Analysis: Why and How. [email protected] www.ircam.fr/equipes/repmus/ lartillot

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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. - PowerPoint PPT Presentation

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Page 1: Perceptive Strategies in Computational Motivic Analysis: Why and How

Perceptive Strategiesin Computational Motivic Analysis:

Why and How.

[email protected]

www.ircam.fr/equipes/repmus/lartillot

Page 2: Perceptive Strategies in Computational Motivic Analysis: Why and How

Perceptive Strategiesin 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.

Page 3: Perceptive Strategies in Computational Motivic Analysis: Why and How

Perceptive Strategiesin Computational Motivic Analysis:

Why and How.

[email protected]

www.ircam.fr/equipes/repmus/lartillot

Page 4: Perceptive Strategies in Computational Motivic Analysis: Why and How

Computational Motivic Analysis

• Automated Music Analysis

• Motivic Analysis– Rudolph Reti– Nicolas Ruwet: Paradigmatic Analysis

• Musical Pattern Discovery– Exact Pattern– Dynamic Programming

Page 5: Perceptive Strategies in Computational Motivic Analysis: Why and How

Dynamic Programming

ACGGCGTTACGGCAGCGCTGATCGTATCTAGCTAGTCTATGCTAT

ACGGCGTTACGAGCAGCGCTGATCGTATCTAGTAGTCTATGCGAT

CDEFGFEADGAGFEF?

Page 6: Perceptive Strategies in Computational Motivic Analysis: Why and How

Automated Music Analysis

• Motivic Analysis– Rudolph Reti– Nicolas Ruwet: Paradigmatic Analysis

• Musical Pattern Discovery– Exact Pattern– Dynamic Programming

Perceptual Model?

Page 7: Perceptive Strategies in Computational Motivic Analysis: Why and How

Music Semiology

ScoreComposer Listener

Poietic Level Neutral Level Esthesic Level

Immanent Structures?

Cultural Knowledge

Cognitive Constraints

Page 8: Perceptive Strategies in Computational Motivic Analysis: Why and How

Immanent Structures?

Transcendent Structures!

Good patterns

Bad patterns

Page 9: Perceptive Strategies in Computational Motivic Analysis: Why and How

Automated Music Analysis

• Motivic Analysis– Rudolph Reti– Nicolas Ruwet: Paradigmatic Analysis

• Musical Pattern Discovery– Exact Pattern– Dynamic Programming

Perceptual Model

Page 10: Perceptive Strategies in Computational Motivic Analysis: Why and How

Perceptive Strategiesin Computational Motivic Analysis:

Why and How.

[email protected]

www.ircam.fr/equipes/repmus/lartillot

Page 11: Perceptive Strategies in Computational Motivic Analysis: Why and How

Temporal Approach

Page 12: Perceptive Strategies in Computational Motivic Analysis: Why and How

Temporal Approach

Page 13: Perceptive Strategies in Computational Motivic Analysis: Why and How

Apprehensive Retention

Page 14: Perceptive Strategies in Computational Motivic Analysis: Why and How

Apprehensive Retention

Page 15: Perceptive Strategies in Computational Motivic Analysis: Why and How

Reproductive Remembering

Page 16: Perceptive Strategies in Computational Motivic Analysis: Why and How

Objectivation

Page 17: Perceptive Strategies in Computational Motivic Analysis: Why and How

Recognitive Remembering

Page 18: Perceptive Strategies in Computational Motivic Analysis: Why and How

Recognitive Remembering

Page 19: Perceptive Strategies in Computational Motivic Analysis: Why and How

Pattern Repetition

Page 20: Perceptive Strategies in Computational Motivic Analysis: Why and How

Abstract Pattern

Page 21: Perceptive Strategies in Computational Motivic Analysis: Why and How

Abstract Pattern Tree

Page 22: Perceptive Strategies in Computational Motivic Analysis: Why and How

Pattern Occurrence Chain

Page 23: Perceptive Strategies in Computational Motivic Analysis: Why and How

Parallel Patterns

Page 24: Perceptive Strategies in Computational Motivic Analysis: Why and How

Architecture• loop for note in score

– memorize new retentions– develop current expected occurrences– develop current unexpected occurrences– develop current objectivations– find new objectivations

Page 25: Perceptive Strategies in Computational Motivic Analysis: Why and How

OMkanthus 0.1