A genetic algorithm for audio retargeting

  • Authors:
  • Stephan Wenger;Marcus Magnor

  • Affiliations:
  • Technische Universität Braunschweig, Braunschweig, Germany;Technische Universität Braunschweig, Braunschweig, Germany

  • Venue:
  • Proceedings of the 20th ACM international conference on Multimedia
  • Year:
  • 2012

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Abstract

We present an audio retargeting technique to create custom soundtracks for movies and games from existing audio material (typically music) by automatically rearranging audio segments. Constraints can be specified to make the length of the audio fit the length of a movie scene, or to align parts of a piece of music with particular events. Existing approaches typically create soundtracks with many unnecessary and often disruptive transitions. We extend a recent analysis and resynthesis method with a novel genetic algorithm for finding an optimal succession of audio segments that minimizes the number of audible transitions and repetitions as well as the deviation from user-specified constraints. Compared to prior work, our experiments with audio examples from different musical genres show a significant improvement with respect to the optimization criteria, and the resulting soundtracks contain few, if any, noticeable transitions.