metadata
language:
- hi
- bn
- gu
- kn
- ml
- mr
- or
- pa
- ta
- te
- en
license: other
license_name: proprietary
license_link: https://fonadalabs.ai
pipeline_tag: automatic-speech-recognition
tags:
- automatic-speech-recognition
- speech-to-text
- indic
- hindi
- api
Kapture v3
Kapture v3 is FonadaLabs' speech recognition model for ten Indian languages and English, built for real conversational audio: call-center recordings, voice notes and voice agents. It is offered as an API; the model weights are not distributed and this repository contains no model files.
- Docs: https://fonadalabs.ai/docs/speech-to-text/kapture-v3
- API key: https://fonadalabs.ai
- Languages: Hindi, Bengali, Gujarati, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu, English
- Output: verbatim transcripts in each language's native script, with segment timestamps
- Audio length: no limit; long recordings are split and transcribed in parallel
Usage
curl -X POST https://api.fonada.ai/v3/asr/transcribe \
-H "Authorization: Bearer $FONADA_API_KEY" \
-F "file=@call.wav" \
-F "language_id=hi"
import os, requests
with open("call.wav", "rb") as audio:
r = requests.post(
"https://api.fonada.ai/v3/asr/transcribe",
headers={"Authorization": f"Bearer {os.environ['FONADA_API_KEY']}"},
files={"file": audio},
data={"language_id": "hi"},
)
print(r.json()["text"])
Results
Self-reported, measured through the production API on 2026-10-22 with each benchmark's official scorer. Word error rate in %, lower is better.
| Benchmark | Metric | Kapture v3 |
|---|---|---|
| Voice Arena Monsoon hi-IN | OI-WER | 6.21 |
| Vaani Benchmark V1.0 (Hindi) | WER, 3 references | 13.1 |
| Vistaar, 8,055-clip sample, 10 languages | WER, Sarvam normalizer | 17.43 |
Open ASR Leaderboard results will be added once the leaderboard maintainers have evaluated the API.
Median server processing time for a short clip is about 0.1 s.