What is XMusic
XMusic is an AI general composition framework independently developed by Tencent Multimedia Laboratory. Users only need to upload any content such as videos, images, text, tags, or humming, and XMusic can generate high-quality music with controllable emotion, genre, and rhythm. Based on self-developed multimodal and sequence modeling technologies, it can parse the prompt content into a symbolic music element space, and use this as a control condition to guide the model in generating rich, precise, and pleasant music, meeting commercial-grade music generation capability requirements. XMusic is suitable for many scenarios such as video editing soundtracks, ambient music selection for shopping malls and venues, interactive entertainment, assisted creation, music education, and music therapy. It can greatly lower the threshold for music creation, enable AI-assisted creation anytime and anywhere, and create a personal exclusive "walking music library".
Main Features of XMusic
- Multimodal input music generation: Supports multiple modal contents such as images, text, videos, tags, and humming as prompts to generate high-quality music with controllable emotion. For example, by entering the description "full of fun and hilarious, making people laugh out loud," XMusic will generate a piece of music with a playful rhythm and cheerful melody.
- Controllable emotion, genre, and rhythm: Users can generate music with specific emotions, genres, and rhythms according to their needs, meeting music usage needs in different scenarios.
- Commercial-grade music generation capability: Based on self-developed multimodal and sequence modeling technologies, XMusic can parse the prompt content into a symbolic music element space, and use this as a control condition to guide the model in generating rich, precise, and pleasant music, meeting commercial-grade music generation capability requirements.
Technical Principles of XMusic
- Core framework: Based on a locally deployed Transformers algorithm framework, this framework has powerful natural language processing capabilities and cross-modal learning capabilities, providing a solid foundation for music generation.
- Core components：
- XProjector: Parses various forms of prompts (such as images, videos, text, tags, and humming) into symbolic music elements (such as emotion, genre, rhythm, and notes) to generate matching music within a projection space.
- XComposer: Includes a generator and a selector. The generator generates music with controllable emotion and beautiful melody based on an innovative symbolic music representation; the selector identifies high-quality symbolic music by constructing a multi-task learning scheme involving quality assessment, emotion recognition, and genre recognition tasks.
- Operating mechanism: Divided into three stages: parsing, generation, and screening. The parsing stage is based on natural language processing and image recognition technologies, analyzing the user-input prompts and mapping them to the symbolic music element projection space; in the generation stage, the generator maps music elements to symbolic music representation sequences, and the decoder generates matching music melodies and rhythms based on these representation sequences; in the screening stage, the selector performs quality assessment on the generated batch of music and screens out the music with the highest quality and the best fit for user needs.
XMusic Project Address
- Project official website：https://xmusic-project.github.io
- arXiv technical paper：https://arxiv.org/pdf/2501.08809
Application Scenarios of XMusic
- Interactive entertainment: In interactive entertainment scenarios, corresponding music can be generated according to the user's interactive behavior or input, enhancing the interactive experience.
- Assisted creation: Provides inspiration and assistance to music creators, helping them quickly generate music materials and improve creation efficiency.
- Music education: Music teachers can use XMusic to generate diverse rhythm, beat, and pitch practice pieces, and combine them with actual teaching scenarios to leverage the teaching-assistance capabilities of AI-generated music.
- Music Therapy: Generate corresponding music according to therapeutic needs to assist the music therapy process.