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Interview transcription with speaker labels

Use interview transcription to prepare recordings for qualitative research. Upload the file and set diarize to true for speaker labels and timestamps. Export text or JSON for coding, and review quotes against the audio.

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  • Speaker labels with diarize
  • Timestamps back to the recording
  • Uploaded media deleted after 24 hours

How it works

Speaker diarization
diarize labels who said what as Speaker 1, Speaker 2 and so on in JSON, text, SRT and VTT.
Back to the audio
Every segment has start and end times, so a quote can be checked against the recording.
Long sessions
Upload files up to 2 GB in resumable chunks. AI transcription accepts media up to 5 hours.
Many languages
Leave language on auto, or pass an ISO 639-1 code. Each segment reports its language.
Media you can delete
Uploaded media is deleted 24 hours after the transcription ends, and you can delete a transcript at any time.
Batch friendly
Add a webhook_url and process a folder of interviews without polling.

Upload

Transcribe research interviews with speaker labels

Files up to 95 MB go in one request. Larger recordings use a chunked upload with the same options.

cURL
curl -X POST "https://api.transcript1.com/v1/transcriptions?wait=60" \
  -H "Authorization: Bearer $TRANSCRIPT1_API_KEY" \
  -F [email protected] \
  -F diarize=true \
  -F language=auto

Read

Labeled lines with timestamps

The text format is easy to paste into analysis tools. Each line starts with the time and the speaker.

format=text&timestamps=true
[00:00:00] Speaker 1: Thanks for making time today.
[00:00:03] Speaker 2: Happy to help.

Structured

Qualitative research transcription in JSON

For coding in your own tools, use the JSON transcript. It lists the speakers and gives every segment a speaker, a language and start and end times.

Response (shortened)
{
  "transcript": {
    "speakers": ["Speaker 1", "Speaker 2"],
    "segments": [
      { "start": 0, "end": 3.4, "speaker": "Speaker 1", "language": "en", "text": "Thanks for making time today." }
    ]
  }
}

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Frequently asked questions

Something missing? Ask support

Are speakers named?

They are labeled Speaker 1, Speaker 2 and so on. transcript1 does not know who they are, so map the labels to participants yourself.

Can I transcribe an interview recorded on my computer?

Yes. Upload the interview recording from the dashboard or API. The API accepts one request up to 95 MB or chunks up to 2 GB. transcript1 processes the uploaded recording; it does not join meetings.

What happens to my recordings?

Uploaded media is deleted 24 hours after the transcription reaches a final status. The transcript is kept until you delete it.

Should I review the transcript?

Yes. Machine transcripts can contain mistakes, so check quotes against the recording before you publish them.

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