A genetic algorithm for audio retargeting

S. Wenger, M. Magnor
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引用次数: 10

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.
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音频重定向的遗传算法
我们提出了一种音频重定向技术,通过自动重新排列音频片段,从现有音频材料(通常是音乐)中为电影和游戏创建自定义音轨。可以指定约束以使音频的长度适合电影场景的长度,或者将音乐的某些部分与特定事件对齐。现有的方法通常会创建带有许多不必要且经常具有破坏性的过渡的音轨。我们用一种新的遗传算法扩展了最近的分析和重新合成方法,用于寻找音频片段的最佳连续,从而最大限度地减少可听过渡和重复的数量,以及与用户指定约束的偏差。与之前的工作相比,我们对来自不同音乐类型的音频示例的实验显示,在优化标准方面有了显著的改进,并且最终的音轨包含很少(如果有的话)明显的过渡。
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