Creating a composition with a trained model using an AWS DeepComposer Music studio experience - AWS DeepComposer

Creating a composition with a trained model using an AWS DeepComposer Music studio experience

To generate, create, and edit compositions with AWS DeepComposer, you use the AWS DeepComposer music studio. To get started, you need a trained model and an input track.

For the model, you can use either a sample or a custom model. This topic covers how to use a sample model. Sample models are available in both AWS DeepComposer music studio experiences.

For the input track, you can use a sample track, record a custom track, or import a track.

Each AWS DeepComposer music studio experience supports three different generative AI techniques, generative adversarial networks (GANs), autoregressive convolutional neural network (AR-CNN), and Transformers. You can use the GANs technique to create accompaniment tracks. You can use the AR-CNN technique to modify notes in your input track. You can use the Transformers technique to extend your input track by up to 30 seconds.

To learn more about how to use the different generative techniques together, see the Generative techniques in AWS DeepComposer topic. The topic covers how to collaborate interactively with the available generative techniques in AWS DeepComposer. You can also learn how to best use the different techniques together.

In each of the following topics, you can find directions for using either AWS DeepComposer Music studio experience.