How Meta’s AI Generates Music Based on a Reference Melody

<h1>MusicGen by Meta</h1> On June 13th, 2023, Meta (formerly Facebook) made waves in the music and AI communities with the release of their generative music model, MusicGen. This model not only surpasses Google’s MusicLM, which was launched earlier this year, in terms of capabilities but is also trained on licensed music data and open-sourced for non-commercial use. This means that you can not only read the <a href="https://arxiv.org/abs/2306.05284" rel="noopener ugc nofollow" target="_blank">research paper</a> or listen to <a href="https://ai.honu.io/papers/musicgen/" rel="noopener ugc nofollow" target="_blank">demos</a> but also copy their code from <a href="https://github.com/facebookresearch/audiocraft" rel="noopener ugc nofollow" target="_blank">GitHub</a> or experiment with the model in a web app on <a href="https://huggingface.co/spaces/facebook/MusicGen" rel="noopener ugc nofollow" target="_blank">HuggingFace</a>. In addition to generating audio from a text prompt, MusicGen can also generate music based on a given reference melody, a feature known as melody conditioning. In this blog post, I will demonstrate how Meta implemented this useful and fascinating functionality into their model. But before we delve into that, let’s first understand how melody conditioning works in practice. <a href="https://medium.com/towards-data-science/how-metas-ai-generates-music-based-on-a-reference-melody-de34acd783">Read More</a>