Speech-to-Text
Speech-to-Text is a app in the osFoundry community catalog. Self-hosted speech-to-text service running OpenAI's Whisper models — accurate transcription in 90+ languages, speaker diarization (optional), VAD-trimmed faster inference, multiple model sizes (tiny → large-v3), REST API + browser upload UI. Powered by the Whisper ASR Webservice (ahmetoner/whisper-asr-webservice). CPU is workable for medium models; GPU is needed for large + real-time.
Details
- Workspace: osfoundry
- Category: COMMUNICATION
- Pricing: Free
- Access: Community
Features
- Speaker diarization (optional)
- VAD-trimmed faster inference
- Multiple model sizes (tiny → large-v3)
- REST API + browser upload UI
Documentation
# Speech-to-Text
Self-hosted Whisper transcription, powered by the Whisper ASR Webservice.
## Performance
- **tiny / base** — usable on CPU (real-time-ish)
- **small / medium** — CPU works for batch transcription; GPU for real-time
- **large-v3 / distil-large-v3** — GPU strongly recommended
## Features
- 90+ languages
- Speaker diarization (optional, via pyannote.audio)
- VAD (voice activity detection) to skip silence + speed up batch jobs
- Output formats: JSON, text, SRT, VTT, TSV
- REST API: POST audio file → returns transcript
- Browser upload UI at `/`
## Packaging
Thin wrapper around the official `onerahmet/openai-whisper-asr-webservice` image (CPU variant). Downloaded models cached at `/root/.cache`.
How to use Speech-to-Text in osFoundry
Install Speech-to-Text into your workspace in one click, then fork it in osStudio to customise the prompts, tools, or configuration for your stack. Anyone in your workspace can pick up where you left off.
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