The advent of ML music models such as Google Magenta's MusicVAE now allow us to extract and replicate compositional features from otherwise complex datasets. These models allow computational composers to parameterize abstract variables such as style and mood. By leveraging these models and combining them with procedural algorithms from the last few decades, it is possible to create a dynamic song that composes music in real-time to accompany interactive experiences. Malakai is a tool that helps users of varying skill levels create, listen to, remix and share such dynamic songs. Using Malakai, a Composer can create a dynamic song that can be interacted with by a Listener
翻译:谷歌 Magenta 的 MusicVAE 等 ML 音乐模型的出现让我们现在能够从其他复杂的数据集中提取和复制组成特征。 这些模型允许计算式作曲家将风格和情绪等抽象变量参数化。 通过利用这些模型并将这些模型与过去几十年的程序算法结合起来,可以创建一首动态歌曲,实时创作音乐,伴随互动体验。 Malakai是一个帮助不同技能水平的用户创建、倾听、重新组合和分享这些动态歌曲的工具。 使用Malakai, 一位作曲家可以创建一首能与聆听者互动的动态歌曲。