DeepFilterNet3
DeepFilterNet3 is an open-source speech enhancement model that uses deep filtering to suppress noise in full-band audio at up to 48 kHz sampling rate. The neural network predicts dynamic suppression gains for each frequency bin, processing 20 ms frames with a 10 ms hop for real-time operation. It achieves high speech intelligibility (STOI 0.944) with minimal residual artifacts. Suitable for video call cleanup, podcast post-production, interview transcription preprocessing, and voice-over enhancement.
Why use DeepFilterNet3 for audio?
Natural voice generation
DeepFilterNet3 produces expressive, high-quality audio suitable for character dialogue, narration, and voiceover work.
Flexible content types
Supports a range of use cases from in-game dialogue and cinematics to marketing narration and social media content.
Fast iteration
Generate and refine audio content quickly, enabling rapid prototyping of character voices and sound design.
Character voiceover and dialogue production
Generate expressive character voices for in-game dialogue, cutscenes, and interactive narratives. Iterate on tone and delivery rapidly.
Marketing narration and promotional audio
Create professional voiceovers for trailers, app store videos, and social media content without booking voice talent.
Sound design exploration and prototyping
Quickly prototype sound effects, ambient audio, and musical elements to test creative directions early in production.