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Cross-modal mappings and audiovisual feedback October 30, 2011 Cross-modal mappings 1 Nick Collins

Cross-modal mappings and audiovisual feedback

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Page 1: Cross-modal mappings and audiovisual feedback

Cross-modal mappings and audiovisual feedback

October 30, 2011 Cross-modal mappings

1

Nick Collins

Page 2: Cross-modal mappings and audiovisual feedback

Summary

  Experiments in audiovisual combination and data flow

  Challenges of audiovisual mapping

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Theoretical backdrop

  Film music vs music film

  1-1 mappings, mickey-mousing, synchresis

  Meanings in parallel, audiovisual objects

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Problems with mapping

  Maps between domains are usually not homomorphisms; not structure-preserving

  Sonification/visualisation from data, audio driving visuals or vice versa; all examples of potentially incompatible spaces

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Psychological backdrop

  Synaesthesia is personal, not universal

  Audiovisual integration, attentional resources

  Coping with multiple objects in counterpoint

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Some successful close audiovisual integrations?

  Coldcut/Hex Timber (1997)

  Autechre/Alex Rutterford Gantz Graf (2002)

  chdh’s audiovisual objects

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Now…

  Some unsuccessful relations?

  Case studies from experiments

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Case 1: PhotoNoise iPad app

  Image -> sound via pixel data

  Multi-touch -> RGB + intensity -> nonlinear oscillators

  Quirky, noisy, more of an esoteric instrument than deep in itself

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Audiovisual feedback

  Round a processing chain incorporating both audio and video material and its analysis

  E.g., audio input -> audio analysis -> drive generative graphics -> video analysis -> drive audio synthesis -> audio input …

  Processing delays

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A V

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Case 2: klipp av (2002-2009)

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Audiovisual performance score

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Case 3: iterative cross-convolution

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With onset detection

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Case 4: audiovisual concatenative synthesis

  Concatenative synthesis = feature-matched substitution of an input from a database

  Usually audio or visual alone.

  Has been explored where video is brought along for free (Grierson and Casey 2007, Scrambled Hackz et al.)

  Can do both at once = audio and video feature data muddle

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Case 5: auto aligned video

  Take an existing music work

  Extract audio features -> drive frame by frame rendering of generative graphics

  End up with close correlation

  Tool chain: SCMIR->Processing->ffmpeg

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What is coming out of this?

  1-1 mapping might be simple, but it is perceptually strong!

  Need for audiovisual objects as coherent entities

  Details of many mappings lost (can be other reasons to keep on regardless, e.g. improvisation in complexity)

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Conclusions

  Considered some of the challenges of correlating audio and visual

  Discussed some projects of varying effectiveness

  Details often lost when mapping between modalities

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Think you for lastening

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http://www.sussex.ac.uk/Users/nc81/researchav.html

Alexander, A., and Collins, N. (2007) Live Audiovisuals. Book chapter in N.Collins and J. d'Escrivan (Eds.) (2007) The Cambridge Companion to Electronic Music

(2007) "Audiovisual Concatenative Synthesis". Proceedings of ICMC2007, International Computer Music Conference, Copenhagen.

(2006) Nick Collins and Fredrik Olofsson. "klipp av: Live Algorithmic Splicing and Audiovisual Event Capture", Computer Music Journal 30(2): pp 8-18

http://www.sussex.ac.uk/Users/nc81/iphone.html#PhotoNoise