Upgrade to Pro — share decks privately, control downloads, hide ads and more …

Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings

Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings

Jaime Arias Almeida

June 27, 2016
Tweet

More Decks by Jaime Arias Almeida

Other Decks in Research

Transcript

  1. Automatic Construction of Interactive Machine
    Improvisation Scenarios from Audio Recordings
    Jaime Arias, Myriam Desainte-Catherine and Shlomo Dubnov
    Université de Bordeaux, LaBRI, UMR 5800
    Inria - Bordeaux Sud-Ouest
    University of California, San Diego, CREL
    MuMe Workshop
    International Conference on Computational Creativity
    June 27, 2016

    View Slide

  2. Motivation
    Dynamic Models of Creativity
    Figure: Human-(Musical) Robot Control: Information Exchange for Meta-Creation
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 1/20
    1/20

    View Slide

  3. Motivation
    Umberto Eco: The Poetics of the Open Work
    Figure: An incomplete knowledge of the system is an essential feature
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 2/20
    2/20

    View Slide

  4. Motivation
    Stockhausen: Klavierstcke XI
    Figure: Mobile structure and graphic layout in 19 fragments
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 3/20
    3/20

    View Slide

  5. Introduction
    Overview of the system
    • PyOracle: https://gitlab.com/himito/PyOracle_I-score
    • i-score: https://github.com/himito/i-score
    • VMO-Score: https://himito.github.io/vmo_i-score_generator
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 4/20
    4/20

    View Slide

  6. Introduction
    Overview of the system
    Pre-Recorded
    Audio
    Variable Markov
    Oracle (VMO)
    Audio
    Segmentation
    Audio
    Oracle
    SNAKES
    Petri Net Model
    input
    output
    output
    input
    output
    Configuration
    File
    output
    (a) Generation of the structure
    Petri Net Model
    Offline
    Improviser
    output
    input
    input
    Audio
    Synthesizer
    Audio File
    output
    input
    Audio Oracle
    input
    Petri Net
    Parameters
    Actions
    Oracle
    Parameters
    Performer Controls
    Configuration File
    Oracle Regions
    Sequence
    Audio
    Buffer
    input
    (b) Offline improvisation
    Figure: Improvisation
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 5/20
    5/20

    View Slide

  7. Introduction
    Overview of the system
    Pre-Recorded
    Audio
    Variable Markov
    Oracle (VMO)
    Audio
    Segmentation
    Audio
    Oracle
    SNAKES
    Petri Net Model
    input
    output
    output
    input
    output
    Configuration
    File
    output
    (a) Generation of the structure
    Petri Net
    Model
    Audio
    Oracle
    i-score
    Petri Net
    Parameters
    Configuration File
    PyOracle
    input
    input
    input
    Real-time
    Performer Controls
    input
    input
    inout
    Real-time Audio
    Output
    Output
    (b) Real-time improvisation
    Figure: Composition
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 6/20
    6/20

    View Slide

  8. Composition

    View Slide

  9. Composition
    Audio Recording
    Figure: Audio recording: Philou.
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 7/20
    7/20

    View Slide

  10. Composition
    PyOracle Improviser
    Figure: Segmentation
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 8/20
    8/20

    View Slide

  11. Composition
    Segmentation
    Figure: Segmentation
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 9/20
    9/20

    View Slide

  12. Composition
    Petri Net
    G
    D
    C
    t
    (a) The marking before firing the enabled
    transition t.
    G
    D
    C
    t
    (b) The marking after firing transition t,
    where t is disabled.
    Figure: Illustration of a firing rule in a Petri Net.
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 10/20
    10/20

    View Slide

  13. Composition
    Petri Net
    Figure: Segmentation
    end
    init
    t1
    t0
    t2
    t3
    t4 t5
    t6
    t7
    t8
    t9
    t10
    t11
    Figure: Timed Petri Net
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 11/20
    11/20

    View Slide

  14. Composition
    Parameters of the Petri Net
    1
    # file: configuration.yml
    2
    3
    conditions:
    4
    - transition : 't0'
    5
    time-min : 0.0
    6
    time-max : 3.0
    7
    condition : '/device/key == 10'
    8
    9
    - transition : 't1'
    10
    ...
    init t0
    [0.0, 3.0]
    /device/key == 10
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 12/20
    12/20

    View Slide

  15. Offline Improvisation

    View Slide

  16. Offline Improvisation
    Specification of actions
    1
    # file: configuration.yml
    2
    3
    actions:
    4
    - address : '/volume/sensor/pos_x'
    5
    value : 10
    6
    time : 250
    7
    8
    - address : ...
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 13/20
    13/20

    View Slide

  17. Offline Improvisation
    Adding environment
    init t0
    /device/key == 10
    [0.0, 3.0]
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 14/20
    14/20

    View Slide

  18. Offline Improvisation
    Adding environment
    (a) human-robot interaction
    init
    env
    t0
    (a,v,t)
    /device/key == 10
    [0.0, 3.0]
    (b) i-score
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 15/20
    15/20

    View Slide

  19. Offline Improvisation
    Adding environment
    init
    env
    t0
    (a,v,t)
    (a == /device/key) ∧ (v == 10) ∧ (t == get_time())
    [0.0, 3.0]
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 16/20
    16/20

    View Slide

  20. Offline Improvisation
    Adding environment
    init
    env
    t0
    (a,v,t)
    te
    (a,v,t)
    get_time() > t
    (a == /device/key) ∧ (v == 10) ∧ (t == get_time())
    [0.0, 3.0]
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 17/20
    17/20

    View Slide

  21. Real-time Improvisation

    View Slide

  22. Real-time Improvisation
    The inter-media sequencer i-score
    score /
    Initial Transition
    T10
    T6
    T5
    T8
    T4
    T2
    T1
    T9
    T7
    T11
    Popolari61oreweed40
    Loop pattern
    snozzle24ambier35
    Loop pattern
    pronger64inurbane46
    Loop pattern
    spouty57carthame37
    Loop pattern
    T5
    T6
    T10
    T1
    T2
    T4
    T8
    T11
    T7
    T9
    T3
    scissel86thermo23
    Loop pattern
    T3
    (c) i-score
    end
    init
    t1
    t0
    t2
    t3
    t4 t5
    t6
    t7
    t8
    t9
    t10
    t11
    (d) Petri net
    Figure: i-score representation.
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 18/20
    18/20

    View Slide

  23. Real-time Improvisation
    The inter-media sequencer i-score
    score /
    Initial Transition
    T10
    T6
    T5
    T8
    T4
    T2
    T1
    Popolari61oreweed40
    Loop pattern
    snozzle24ambier35
    Loop pattern
    pronger64inurbane46
    Loop pattern
    T5
    T6
    T10
    T1
    T2
    T4
    T8
    (a) i-score
    end
    init
    t1
    t0
    t2
    t3
    t4 t5
    t6
    t7
    t8
    t9
    t10
    t11
    (b) Petri net
    Figure: i-score representation.
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 19/20
    19/20

    View Slide

  24. Concluding Remarks

    View Slide

  25. Concluding Remarks
    • Music as a set of combinatorial processes with concurrency control
    • Improvisation as a stylistic combinatorial system
    • Open form establishes a set of conditions and actions for synchronization
    • Generalizes and automates existing DAW tools (session view - clip, follow...)
    Combinatorial systems date back to ars inventendi (Leibniz) and are the core of ars
    magna (great art) of the Franciscan monk Ramon Llull (1232-1316), as well as the
    ecstatic Kabbalah of Abraham Abulafia (1240-1291), and Renaissance philosophers
    such as Giordano Bruno (1548-1600).
    ’́One should not pay attention to the properties of terms but only to the fact
    that they define an order, a texture, an architecture‘̀ U. Eco, The Search for the
    Perfect Language, Wiley-Blackwell 1997
    Shlomo Dubnov - University of California, San Diego - CREL (2016) Automatic Construction of Interactive Machine Improvisation Scenarios from Audio Recordings 20/20
    20/20

    View Slide

  26. Questions

    View Slide

  27. Thank you for your attention!

    View Slide

  28. Automatic Construction of Interactive Machine
    Improvisation Scenarios from Audio Recordings
    Jaime Arias, Myriam Desainte-Catherine and Shlomo Dubnov
    Université de Bordeaux, LaBRI, UMR 5800
    Inria - Bordeaux Sud-Ouest
    University of California, San Diego, CREL
    MuMe Workshop
    International Conference on Computational Creativity
    June 27, 2016

    View Slide