DD-Shooter is a generative artificial intelligence audio synthesis tool developed by Sonolisk for creating and transforming drum sounds. It uses diffusion model-based machine learning models to generate percussive audio from text descriptions, audio examples, or combinations of conditioning inputs.

Unlike conventional drum sample libraries and drum machines, DD-Shooter employs learned latent representations to synthesize new drum sounds and variations rather than relying solely on prerecorded samples or manually designed synthesis parameters.

The development of DD-Shooter began early 2024 as an online drum synthesis application in the cloud customizing the waveform diffusion model.^[2] on GitHub^[3] The software was initially introduced under audiostein as part of a broader trend toward generative AI systems for music and audio production. Today, DD-Shooter is a standalone and VST/AU plugin from Sonolisk running locally on CPUs.

DD-Shooter utilizes diffusion models for waveform synthesis and transformation. The model generates drum sounds through an iterative denoising process conditioned on user inputs.

Supported conditioning methods include:

• Text prompts describing sonic characteristics
• Audio-guided generation
• Latent-space interpolation between sounds
• Drum sound variation and augmentation
• Audio inpainting and localized editing

DD-Shooter provides:

• Text-to-drum synthesis
• Generation of drum sound variations
• Timbre transfer and transformation
• Prompt-based sound exploration
• Latent interpolation between drum sounds
• Inpainting of selected audio regions

• Artificial intelligence in music
• Audio synthesis
• Music technology
• Drum machine
• Generative artificial intelligence
• Diffusion model