1.1 KiB
1.1 KiB
Audio Denoise Worker (RNNoise / arnndn)
RunPod Serverless CPU worker that removes background noise from audio using
ffmpeg's RNNoise filter (arnndn), with a built-in FFT denoiser (afftdn)
as an automatic fallback.
Contract
- Input:
{"audio": "<base64>"}— any format/sample rate. Adata:...;base64,prefix is stripped automatically. - Output:
{"audio": "<base64 WAV>"}— denoised, 48 kHz mono WAV. - Error:
{"error": "<message>"}.
Pipeline
decode base64 -> temp input file -> ffmpeg -i in -af arnndn=m=/app/models/rnnoise.rnnn -ar 48000 -ac 1 out.wav -> read -> base64.
Deploy
- Dockerfile path:
/workers/audio-denoise/Dockerfile - Build context: repo root (
docker build -f workers/audio-denoise/Dockerfile .) - GPU: none (CPU-only worker)
- App env var to set:
RUNPOD_AUDIO_DENOISE_URL(your deployed endpoint URL)
Model
The Dockerfile downloads the beguiling-drafts RNNoise model from
GregorR/rnnoise-models to /app/models/rnnoise.rnnn. If that download
fails at build time, the handler transparently falls back to ffmpeg's
built-in afftdn FFT denoiser (no model file needed).