---
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

```bash
curl -X POST https://api.fonada.ai/v3/asr/transcribe \
  -H "Authorization: Bearer $FONADA_API_KEY" \
  -F "file=@call.wav" \
  -F "language_id=hi"
```

```python
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](https://huggingface.co/datasets/VoiceArena/Monsoon_hi_test) | OI-WER | 6.21 |
| [Vaani Benchmark V1.0](https://huggingface.co/datasets/ARTPARK-IISc/Vaani-Benchmark-V1.0) (Hindi) | WER, 3 references | 13.1 |
| [Vistaar](https://github.com/AI4Bharat/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.