Today on the show I have the pleasure to talk to returning guest, Taylor Peer one of the co-founders of the startup, behind Beat Shaper.

Taylor will explain how they are following an Bottom-up approach to create electronic music, giving producers, fine grained control to create individual music instruments and beat patterns. For this, Beat Shaper is combining Variational Auto-encoders and Transformers. The VAE is used to create high dimensional embeddings that represent the users preferences that are used to guide the autoregressive generation process of the Transformer. The token sequence generated with the transformer is a custom developed symbolic music notation that can be decoded into individual instruments.

We discuss in detail the system architecture and training process. Taylor is explaining in depth how they build such a system, and how they have been creating their own synthetic training dataset that contains music in symbolic notation that enables the fine grained control over the generated music.

I hope you like this episode, and find it useful.

### References

beatshaper.ai - Beatshaper an Copilot for Musics Producers

https://openai.com/index/musenet/ - OpenAI MuseNet

Please create a funny looking comic image, showing a panda with glasses that is very busy creating music on a computer.