Music Representing Corpus Virtual: An Open Sourced Library for Explorative Music Generation, Sound Design, and Instrument Creation with Artificial Intelligence and Machine Learning
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Abstract (arXiv)
Music Representing Corpus Virtual (MRCV) is an open source software suite designed to explore the capabilities of Artificial Intelligence (AI) and Machine Learning (ML) in Music Generation, Sound Design, and Virtual Instrument Creation (MGSDIC). The software is accessible to users of varying levels of experience, with an emphasis on providing an explorative approach to MGSDIC. The main aim of MRCV is to facilitate creativity, allowing users to customize input datasets for training the neural networks, and offering a range of options for each neural network (thoroughly documented in the Github Wiki). The software suite is designed to be accessible to musicians, audio professionals, sound designers, and composers, regardless of their prior experience in AI or ML. The documentation is prepared in such a way as to abstract technical details, thereby making it easy to understand. The software is open source, meaning users can contribute to its development, and the community can collectively benefit from the insights and experience of other users.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 22 references that are in the map. First posted on arXiv 24 May 2023.
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5 of 22 references.
References · 5
- 2014Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modelingcited by 2,341
- 2018Enabling Factorized Piano Music Modeling and Generation with the MAESTRO Datasetcited by 215
- 2021RAVE: A variational autoencoder for fast and high-quality neural audio synthesiscited by 72
- 2021MixMo: Mixing Multiple Inputs for Multiple Outputs via Deep Subnetworkscited by 32
- 2017Brain Intelligence: Go Beyond Artificial Intelligencecited by 9
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