DiffRhythm-full

A diffusion-based model for high-quality rhythm generation in music

AI-Powered Rhythm Generation

DiffRhythm-full generates realistic and diverse rhythm patterns for music composition

Live Demo

Generate rhythm patterns by specifying your preferences:

60 120 200

Output Preview

Generated Rhythm

Pop • 120 BPM • Medium complexity

Features

Why Choose DiffRhythm-full?

Advanced AI capabilities for professional music production

Diffusion-Based

Utilizes state-of-the-art diffusion models for high-quality rhythm generation

Parameter Control

Fine-tune generation with tempo, genre, and complexity parameters

Multi-Instrument

Generates coordinated rhythms across drum kits and percussion instruments

MIDI Export

Export generated rhythms as MIDI files for use in any DAW

Diverse Styles

Capable of generating everything from simple beats to complex polyrhythms

AI-Powered

Trained on extensive datasets of professional rhythm patterns

API Integration

Easily integrate DiffRhythm-full into your applications

Python Example

Generate rhythms programmatically with our Python API:

from diffrhythm import DiffRhythmGenerator

# Initialize the generator
generator = DiffRhythmGenerator.from_pretrained("ASLP-lab/DiffRhythm-full")

# Generate a rhythm pattern
params = {
    "genre": "rock",
    "tempo": 110,
    "complexity": "medium",
    "duration": 8  # bars
}

rhythm = generator.generate(**params)

# Save as MIDI
rhythm.save("output.mid")

API Parameters

genre

Specifies the musical genre for the rhythm (e.g., pop, rock, jazz, electronic)

tempo

Beats per minute (BPM) for the generated rhythm (range: 60-200)

complexity

Controls the rhythmic complexity (simple, medium, complex)

duration

Length of the generated rhythm in musical bars

instruments

Optional list of percussion instruments to include

Full API Documentation

Research

The Science Behind DiffRhythm

Cutting-edge AI research in music generation

Research Paper

Learn about the architecture and training methodology

Read paper

Model Performance

Evaluation metrics and comparative analysis

View details

Model Architecture

Technical details of the diffusion model implementation

GitHub repository

Research Team

ASLP-Lab at Peking University

Visit lab website

Ready to integrate DiffRhythm? Start generating professional rhythms today.

Available on Hugging Face for easy integration into your projects.

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