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What does it do?

  • Music Generation
  • Singing Synthesis
  • Lyrics Conditioning
  • Audio Compression
  • Artist Style Emulation

How is it used?

  • Input genre
  • artist
  • and lyrics to generate music samples.
  • Download the code
  • input lyrics
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Who is it good for?

  • AI Researchers
  • Musicians
  • Music Producers
  • Audio Engineers
  • Songwriters

What does it cost?

  • Pricing model : Unknown

Details & Features

  • Made By

    OpenAI
  • Released On

    2015-09-22

Jukebox is an advanced AI-powered music generation system developed by OpenAI. This neural network creates original music samples, including rudimentary singing, in various genres and artist styles, utilizing raw audio and conditioning based on genre, artist, and lyrics.

Key features:

- Music Generation: Produces raw audio samples in diverse genres and styles, including vocal elements.
- Lyrics Conditioning: Aligns generated audio with provided lyrical content.
- Artist and Genre Conditioning: Steers music generation towards specific artist styles or genres for improved quality and relevance.
- High-Quality Audio: Generates high-fidelity audio using a hierarchical VQ-VAE compression and upsampling approach.
- Sample Explorer: Provides a tool for exploring uncurated samples generated by the model.
- Curated Samples: Offers a collection of curated samples showcasing the model's capabilities across different styles and lyrical inputs.
- Large Dataset Training: Utilizes a dataset of 1.2 million songs, including metadata such as artist, album, genre, and lyrics.

How it works:

1. Raw audio is compressed into discrete codes using a hierarchical VQ-VAE model.
2. Transformer models generate new music in the compressed space.
3. Generated codes are upsampled back to raw audio, producing high-quality samples.
4. The model incorporates conditioning on artist, genre, and lyrics during training and generation.

Use of AI:
Jukebox employs generative AI techniques, combining VQ-VAE for audio compression with transformer models for music generation. This approach allows the system to handle the complex, long-range dependencies inherent in music creation.

AI foundation model:
The foundation model consists of a hierarchical VQ-VAE combined with transformer-based priors, built on the principles of autoregressive modeling and sparse transformers.

Target users:
- AI and music generation researchers
- Musicians exploring AI-generated music
- Developers integrating music generation capabilities into applications
- Academic institutions and creative collaborators

How to access:
Jukebox is available as open-source code, allowing researchers and developers to experiment with and build upon the model. The model weights, code, and tools for exploring generated samples are publicly accessible.

  • Supported ecosystems
    Google, Android, iOS, Apple, iOS, Apple, Android, Google
  • What does it do?
    Music Generation, Singing Synthesis, Lyrics Conditioning, Audio Compression, Artist Style Emulation
  • Who is it good for?
    AI Researchers, Musicians, Music Producers, Audio Engineers, Songwriters

PRICING

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Pricing model: Unknown

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