DiffRhythm Operational

DiffRhythm is an AI song generation model developed by the ASLP Lab at Northwestern Polytechnical University. It uses lyric text and style prompts as creative inputs to generate complete songs containing both vocals and accompaniment.

The tool uses a latent diffusion model and provides open-source models and inference code. It can be used both for music creation experiments and as a foundation for research and further development.

Users can enter lyrics and guide song generation with style prompts such as “pop” and “folk.” The tool supports Chinese and English songs and can generate complete audio with vocals and accompaniment in a single run, with a maximum length of approximately 4 minutes and 45 seconds.

According to the available materials, a single generation usually takes approximately 10 seconds. The specific output depends on the lyrics, style description, and actual runtime environment.

Music producers can use it to quickly validate song demos and assist with exploring melodic and arrangement directions. Short-video and other content creators can use it to produce background music drafts.

Developers and researchers interested in AI audio can use the open-source models and inference code for research or further development. Music enthusiasts can also start with lyrics and style prompts to experiment with generating complete songs.

DiffRhythm is better suited to creative validation, song demos, and preliminary audio production. Although generated songs include vocals and accompaniment, they may not directly meet every publishing or production requirement. Users should still review and post-process the output based on audio quality, vocal performance, lyric clarity, and overall style.

The project materials do not specify detailed commercial usage terms, output content review mechanisms, or resource requirements for different runtime environments. Relevant rules should be verified independently before formal use.