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Description
AudioCraft serves as a comprehensive codebase tailored for all your generative audio requirements, including music, sound effects, and compression, following its training on raw audio signals. By utilizing AudioCraft, we enhance the design of generative audio models significantly compared to earlier methodologies. Both MusicGen and AudioGen rely on a unified autoregressive Language Model (LM) that functions across streams of compressed discrete music representations known as tokens. We propose a straightforward technique to exploit the intrinsic structure of the parallel token streams, demonstrating that with a single model and a refined interleaving pattern, we can effectively model audio sequences while capturing long-term dependencies, resulting in the generation of high-quality audio outputs. Our models utilize the EnCodec neural audio codec to derive discrete audio tokens from the raw waveform, with EnCodec transforming the audio signal into multiple parallel streams of discrete tokens. This innovative approach not only streamlines audio generation but also enhances the overall efficiency and quality of the output.
Description
We are excited to unveil Jukebox, a cutting-edge neural network designed to create music, including basic vocalization, in diverse genres and artistic expressions as raw audio. Alongside the release of the model weights and code, we are offering a tool to help users explore the music samples generated by Jukebox. By inputting genre, artist, and lyrics, users can receive entirely new music pieces crafted from the ground up. Jukebox is capable of producing a vast array of musical and vocal styles, and it can also generalize to lyrics that were not part of the training dataset. The lyrics included here have been collaboratively crafted by researchers at OpenAI and a language model. When provided with lyrics from its training set, Jukebox generates songs that diverge significantly from the originals, showcasing its creative capabilities. Users can input a 12-second audio clip for Jukebox to build upon, with the final output reflecting a desired style. Our focus on music stems from a desire to advance the potential of generative models further. Utilizing a quantization-based approach called VQ-VAE, Jukebox’s autoencoder model effectively compresses audio into a discrete latent space, enabling innovative sound generation. As we continue to refine these technologies, we look forward to the creative possibilities that lie ahead.
API Access
Has API
API Access
Has API
Integrations
Microsoft Azure
OpenAI
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Meta AI
Founded
2004
Country
United States
Website
audiocraft.metademolab.com
Vendor Details
Company Name
OpenAI
Founded
2015
Country
United States
Website
openai.com/blog/jukebox/