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Arabic speech-to-text API

Upload Arabic audio to POST /v1/audio/transcriptions and read the transcript and measured usage.

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Speech to Text

POST /v1/audio/transcriptions

modelstring

Use arabic asr. Required by OpenAI SDKs.

filemultipart

Audio or video file. The complete multipart upload must fit within 25 MB.

response_formatstring

Optional: json (default, recommended) or text. verbose_json is also accepted but does not add word or segment timestamps.

languagestring

Optional BCP-47 language code. Defaults to ar.

temperaturenumber

Optional sampling temperature. Defaults to 0.

Field	Type	Notes
model	string	Use arabic asr. Required by OpenAI SDKs.
file	multipart	Audio or video file. The complete multipart upload must fit within 25 MB.
response_format	string	Optional: json (default, recommended) or text. verbose_json is also accepted but does not add word or segment timestamps.
language	string	Optional BCP-47 language code. Defaults to ar.
temperature	number	Optional sampling temperature. Defaults to 0.

Prepare a recording with clear Arabic speech. Replace meeting.wav in the example with your local file path. Upload the file as multipart form data; do not send a JSON body or manually set the multipart boundary.

curl --fail --show-error https://api.sawtakarabi.ai/v1/audio/transcriptions \
  -H "Authorization: Bearer sk_ar_live_..." \
  -F model="arabic asr" \
  -F [email protected] \
  -F response_format=json

Example JSON response

{
  "text": "النص المكتوب",
  "usage": { "type": "duration", "seconds": 42 }
}

Transcription is charged after the audio is processed, on usage.seconds, because the duration is not knowable until the file is decoded. Your balance has to cover the longest the upload could be before the request starts.

The json response includes the transcript in text and usage when supplied by the transcription service. With response_format=text, the body is plain text and has no usage object. Neither format provides speaker labels or word timestamps.

Review names, numbers and specialist terms before publishing or using a transcript in an important workflow. Audio quality, overlapping speakers and mixed languages can affect the result.