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Automatic Calibration of Modified FM Synthesis to Harmonic Sounds Using Genetic Algorithms

机译:使用遗传算法自动将修改后的FM合成校准为和声

摘要

Many audio synthesis techniques have been successful inreproducing the sounds of musical instruments. Several of these techniques require parameters calibration. However, this task can be difficult and time-consuming especially when there is not intuitive correspondence between a parameter value and the change in the produced sound. Searching the parameter space for a given synthesis technique is, therefore, a task more naturally suited to an automatic optimization scheme.Genetic algorithms (GA) have been used rather extensively for this purpose, and in particular for calibrating Classic FM (ClassicFM) synthesis to mimic recorded harmonic sounds. In this work, we use GA to further explore its modified counterpart, Modified FM (ModFM), which has not been used as widely, and its ability to produce musical sounds not as fully explored. We completely automize the calibration of a ModFM synthesis model for the reconstruction of harmonic instrument tones using GA. In this algorithm, we refine parameters and operators such as crossover probability or mutation operator for closer match. As an evaluation, we show that GA system automatically generates harmonic musical instrument sounds closely matching the target recordings, a match comparable to the application of GA to ClassicFM synthesis.
机译:许多音频合成技术已经成功地再现了乐器的声音。这些技术中的几种需要参数校准。然而,特别是当参数值与所产生的声音的变化之间没有直观的对应时,该任务可能是困难且耗时的。因此,在参数空间中搜索给定的合成技术是一项自然而然适合自动优化方案的任务。为此,遗传算法(GA)已被广泛使用,尤其是将经典FM(ClassicFM)合成物校准为模仿录制的和声。在这项工作中,我们使用GA进一步探索了尚未被广泛使用的改良型对应物Modified FM(ModFM),以及其产生音乐声音的能力并未得到充分探索。我们完全自动化了使用GA重构ModFM合成模型的校准,以用于谐波乐器音调的重建。在该算法中,我们优化了参数和运算符,例如交叉概率或变异运算符,以实现更紧密的匹配。作为评估,我们证明了GA系统会自动生成与目标录音​​非常匹配的和声乐器声音,这种匹配与GA在ClassicFM合成中的应用相当。

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