In the ever-evolving landscape of artificial intelligence, ByteDance has once again made a significant stride by introducing Seed-Music, an AI music generation giant model. This innovative tool promises to revolutionize the music creation process, making it accessible to both novices and professional musicians.
What is Seed-Music?
Seed-Music is an AI music generation model developed by ByteDance. It has the capability to transform 10-second audio clips into complete music compositions. The model utilizes self-regressive language models and diffusion methods to generate high-quality, style-controlled music based on users’ multi-modal inputs, such as style descriptions, audio references, sheet music, and sound prompts.
The primary goal of Seed-Music is to simplify the music creation process, making it easier for musicians of all levels to compose music. Not only does it generate complete audio compositions, but it also offers music editing features, allowing users to personalize the music they create.
Key Features of Seed-Music
Lyrics and Melody Editing
Users can directly edit lyrics and melodies in the generated audio, enabling personalized music creation.
Zero-Shot Singing Voice Conversion
Seed-Music supports users in converting their voices into expressive singing performances using just 10 seconds of singing or ordinary speech. It can mimic songs of any gender and style.
Symbolic Music Representation
Seed-Music introduces lead sheet tokens as a symbolic music representation, making it easier for users to understand and edit music, including melody, harmony, and rhythm.
Music Structure Editing
Users can edit different parts of the music, such as verses, choruses, and other structural elements, to meet specific creative needs.
Music Style and Emotional Adjustment
Seed-Music allows users to adjust the style and emotion of the generated music to match their creative vision.
Technical Principles of Seed-Music
Auto-regressive Language Model (Auto-regressive Language Model, LM)
This model learns patterns from music data sets to predict the next element in the music sequence, such as notes, rhythm, or chords. In music generation, the auto-regressive model generates a coherent music sequence based on given inputs, such as lyrics, melody fragments, or other music features.
Diffusion Models
These models generate data by gradually removing noise, similar to the physical process of diffusion. In music editing, diffusion models can be used to finely adjust music elements, such as modifying melody or harmony, while maintaining the natural fluidity of the music.
Zero-Shot Learning
In Seed-Music, zero-shot singing voice conversion allows users to convert their own voices into specific singing styles without providing a large amount of sample data.
Multi-modal Input Processing
The system can process and understand various types of input data, such as text, audio, and sheet music, and integrate these data to generate music.
Note-Level Editing
The system provides fine control over music, allowing users to edit music at the note level, including modifying pitch, duration, and dynamics.
Project Address
- Project Website: team.doubao.com/en/special/seed-music
- arXiv Technical Paper: arxiv.org/pdf/2409.09214
Application Scenarios
Personal Music Creation
Music enthusiasts can use Seed-Music to create their own songs without the need for deep music theory or playing skills.
Professional Music Production
Music producers and composers can use Seed-Music to generate music demos, rapid prototyping, or as a source of creative inspiration.
Music Education
Teachers and students can use Seed-Music as a teaching tool to learn music theory and composition skills through practice.
Social Media Content Creation
Content creators can generate unique background music for their social media posts to enhance the attractiveness of visual content.
Advertising and Multimedia Production
Advertisers and multimedia producers can generate customized music and soundtracks for commercial advertisements, videos, movies, and games.
Seed-Music is poised to transform the music industry by making music creation more accessible and efficient. With its advanced technology and user-friendly features, it is expected to attract a wide range of users from different backgrounds.
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