Related papers: Music Representing Corpus Virtual: An Open Sourced Library for Explorative Music Generation, Sound Design, and Instrument Creation with Artificial Intelligence and Machine Learning

Music Representing Corpus Virtual: An Open Sourced Library for Explorative Music Generation, Sound Design, and Instrument Creation with Artificial Intelligence and Machine Learning

URL: http://arxiv.org/abs/2305.14948v1
Date: Wed, 24 May 2023 09:36:04 GMT
Title: Music Representing Corpus Virtual: An Open Sourced Library for Explorative Music Generation, Sound Design, and Instrument Creation with Artificial Intelligence and Machine Learning
Authors: Christopher Johann Clarke
Abstract summary: 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 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. 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.
Score: 0.0
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: 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.