Announcing the AWS DeepComposer Chartbusters challenges 2021 season launch

We’re back with two new challenges for the AWS DeepComposer Chartbusters 2021 season! Chartbusters is a global challenge in which developers use AWS DeepComposer to create original compositions and compete in monthly challenges to showcase their machine learning (ML) and generative artificial intelligence (AI) skills. Regardless of your background in music or ML, one of the two new challenges will be right for you.

You can choose between two different challenges this season. In the basic challenge, Melody-Go-Round, you can use any of the generative AI models available in the AWS DeepComposer Music studio to create new compositions. In the advanced challenge, Melody Harvest, you train a custom generative AI model with your own dataset using Amazon SageMaker. In this challenge, you can dive deeper into the mechanics of data preparation, model training, and evaluation to teach a model to play your favorite style of music.

The 2021 season runs through October 31, 2021. Winners of each challenge are selected on the last day of each month, and we’ll feature the winners in an AWS Machine Learning Blog post. Monthly winners of the Melody Harvest challenge will also win a ticket to AWS re:Invent 2021. To participate, go to the AWS DeepComposer console and choose the Chartbusters challenge that’s right for you in the navigation pane.

Compete in the Melody-Go-Round challenge

You can compete in the AWS DeepComposer Chartbusters Melody-Go-Round challenge in just a few simple steps:

In the AWS DeepComposer Music studio, record a track, import a track, or pick any of the available input tracks.

Get creative and explore different combinations of available models. You can also explore advanced parameters under each model.

Use the Edit melody feature to add or remove notes, or change the note duration and pitch. When finished, choose Apply changes. You can iterate by adjusting the advanced parameters and choosing Enhance again. Repeat these steps until you’re satisfied with the generated music.

You can also download the melody and import it into a digital audio workstation like GarageBand and further indulge your creativity.

When your melody is complete, go to the submission form and choose an existing composition or import a post-processed audio track. Choose Melody-Go-Round for the competition type, register or sign in to SoundCloud, and choose Submit.

For more information on judging criteria, visit AWS DeepComposer Melody-Go-Round page.

Compete in the Melody Harvest challenge

Explore our GitHub pages for Generative Adversarial Networks (GANs), Autoregressive Convolutional Neural Networks (AR-CNNs), and Transformers. Then train your own model and start composing your music.
You can upload the generated MIDI file to a digital audio workstation like GarageBand and further improve it.
When your melody is complete, go to the submission form, choose Melody Harvest for the competition type, import a postprocessed audio track, and add the link to your GitHub repository. Make sure your GitHub repository has your notebook and your model’s checkpoint files.

For more information on datasets and judging criteria visit AWS DeepComposer Melody Harvest page.

Conclusion

Congratulations! You have successfully submitted your composition to the AWS DeepComposer Chartbusters challenge. Now you can invite your friends and family to listen to your creation on SoundCloud, vote for their favorite, and join the fun by participating in the competition.

Although you don’t need a physical keyboard to compete, we’re offering the AWS DeepComposer keyboard at a special price of $69.00 (30% off) for a limited time on Amazon.com to improve your music generation experience. The pricing includes the keyboard and 3 months of the AWS DeepComposer free trial. To learn more about the different generative AI techniques supported by AWS DeepComposer, check out the learning capsules available on the AWS DeepComposer console.

About the Authors

Maryam Rezapoor is a Senior Product Manager with AWS AI Devices team. As a former biomedical researcher and entrepreneur, she finds her passion in working backward from customers’ needs to create new impactful solutions. Outside of work, she enjoys hiking, photography, and gardening.