Malakai: Music That Adapts to the Shape of Emotions

• URL: http://arxiv.org/abs/2112.02070v1
• Date: Fri, 3 Dec 2021 18:34:54 GMT
• Title: Malakai: Music That Adapts to the Shape of Emotions
• Authors: Zack Harris, Liam Atticus Clarke, Pietro Gagliano, Dante Camarena, Manal Siddiqui, Pablo S. Castro
• Abstract summary: Malakai is a tool that helps users to create, listen, remix and share such dynamic songs. Using Malakai, a Composer can create a dynamic song that can be interacted with by a Listener.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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

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