In Fleeting Visions: Deep Neural Music Fickle Play

S. Dubnov
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引用次数: 1

Abstract

We describe a series of short music pieces that is generated in a semi-improvised manner by a computer, using deep representations and temporal memory model constructed from learning a corpus of piano works by Sergei Prokofiev. Inspired by Prokofiev's piece of a similar name, this work explores imaginative capabilities of generative music machine through a series of passing-by sonic visions triggered by fleeting activations of the underlying musical network from a musician performer input. Unlike most other common machine learning and neural music compositions that explore stylistic imitation, the impetus here is to provide a rainbow of unimagined possibilities enabling creative human intervention and interaction with a complex system, realized in a series of improvisations, each with a different form, texture and character.
在稍纵即逝的视觉:深层神经音乐变幻无常的发挥
我们描述了一系列由计算机以半即兴的方式生成的短音乐作品,使用深度表示和时间记忆模型,这些模型是通过学习谢尔盖·普罗科菲耶夫的钢琴作品语料库构建的。受普罗科菲耶夫同名作品的启发,该作品通过一系列经过的声音视觉来探索生成音乐机器的想象能力,这些声音视觉是由音乐家表演者输入的底层音乐网络的短暂激活触发的。与大多数其他常见的机器学习和探索风格模仿的神经音乐作品不同,这里的推动力是提供一系列无法想象的可能性,使创造性的人类干预和与复杂系统的互动成为可能,在一系列即兴创作中实现,每个都有不同的形式,质地和特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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