Speech to Text (STT)

Transcribe an audio recording into text. Useful for meeting recordings, voice notes or subtitle generation.

Basic usage

import os
from openai import OpenAI

client = OpenAI(api_key=os.environ["QEVRON_API_KEY"], base_url="https://app.qevron.ai/v1")

with open("recording.wav", "rb") as f:
    resp = client.audio.transcriptions.create(
        model="solab-stt",
        file=f,
        language="en",
    )
print(resp.text)

With curl

curl https://app.qevron.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $QEVRON_API_KEY" \
  -F "model=solab-stt" \
  -F "file=@recording.wav" \
  -F "language=en"

Verbose output (timestamps)

With response_format=verbose_json you get language, duration and timestamped segments:

curl https://app.qevron.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer $QEVRON_API_KEY" \
  -F "model=solab-stt" \
  -F "file=@recording.wav" \
  -F "response_format=verbose_json"

{
  "task": "transcribe",
  "language": "en",
  "duration": 12.4,
  "text": "Hello, this is a test recording...",
  "segments": [
    { "start": 0.0, "end": 3.2, "text": "Hello, this is a test recording" }
  ]
}

Tips

• Specify language: giving the language upfront improves accuracy (e.g. tr, en).
• Translation: to translate speech into English, use the /v1/audio/translations endpoint.
• Supported formats: wav, mp3, m4a, etc. (model-dependent).

Related: Audio API — STT.