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Getting Started with Deepgram Whisper Cloud

Pre-recorded Streaming:Nova

Using Deepgram’s fully hosted Whisper Cloud instead of running your own version provides many benefits. Some of these benefits include:

  • Pairing the Whisper model with Deepgram features that you can’t get using the OpenAI speech-to-text API, such as diarization and word timings.
  • Support for all Whisper model sizes: tiny, base, small, medium, and large.
  • Support for up to 5 concurrent requests for the Pay As You Go and Growth plans.

Deepgram hosts and maintains these Whisper models; they aren’t hosted or run by Open AI. Therefore, data sent through API requests for our Whisper models will not be sent to OpenAI.

In this guide, you’ll learn how to transcribe pre-recorded audio using Deepgram’s hosted Whisper API.

Transcribe a remote file using Deepgram’s Whisper API with the following request.

Bash

If you would like to use a Deepgram SDK to make the request, follow the steps in the Pre-Recorded speech-to-textguide, but change the model to whisper.

JSON
{
  "metadata": {
    "transaction_key": "deprecated",
    "request_id": "6ba2879c...",
    "sha256": "6a7d98...",
    "created": "2023-04-12T20:33:53.620Z",
    "duration": 96.56319,
    "channels": 1,
    "models": [
      "e04910..."
    ],
    "model_info": {
      "e04910...": {
        "name": "medium-en-whisper",
        "version": "2022-09-21.4",
        "arch": "whisper"
      }
    }
  },
  "results": {
    "channels": [
      {
        "alternatives": [
          {
            "transcript": "another big problem in the speech analytics space when customers first bring the software on is that they are blown away by the fact that an engine can monitor hundreds of kpis ...",
            "confidence": 0.98273027,
            "words": [
              {
                "word": "another",
                "start": 0.06,
                "end": 0.56,
                "confidence": 0.34510013
              },
              {
                "word": "big",
                "start": 0.84,
                "end": 1.3399999,
                "confidence": 0.9840386
              },
              {
                "word": "problem",
                "start": 1.54,
                "end": 2.04,
                "confidence": 0.9970716
              },
            ...
            ]
          }
        ]
      }
    ]
  }
}

To enable Deepgram’s Whisper API, add a model parameter in the query string and set it to model=whisper

Bash

To enable a specific size of the Whisper model, set the model parameter to model=whisper-size.

Bash

These are the Deepgram Whisper Cloud models available:

  • model=whisper (defaults to whisper-medium)
  • model=whisper-tiny
  • model=whisper-base
  • model=whisper-small
  • model=whisper-medium
  • model=whisper-large (defaults to large-v2)

Deepgram Whisper Cloud supports language detection, which means just by setting detect_language=true, your audio will be transcribed in the detected language.

Officially supported languages include Afrikaans, Arabic, Armenian, Azerbaijani, Belarusian, Bosnian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Greek, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Kannada, Kazakh, Korean, Latvian, Lithuanian, Macedonian, Malay, Marathi, Maori, Nepali, Norwegian, Persian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swahili, Swedish, Tagalog, Tamil, Thai, Turkish, Ukrainian, Urdu, Vietnamese, and Welsh. (Source: “Whisper API FAQ”)

Languages supported by whisper include: en, zh, de, es, ru, ko, fr, ja, pt, tr, pl, ca, nl, ar, sv, it, id, hi, fi, vi, he, uk, el, ms, cs, ro, da, hu, ta, no, th, ur, hr, bg, lt, la, mi, ml, cy, sk, te, fa, lv, bn, sr, az, sl, kn, et, mk, br, eu, is, hy, ne, mn, bs, kk, sq, sw, gl, mr, pa, si, km, sn, yo, so, af, oc, ka, be, tg, sd, gu, am, yi, lo, uz, fo, ht, ps, tk, nn, mt, sa, lb, my, bo, tl, mg, as, tt, haw, ln, ha, ba, jw, su.

If you would like to transcribe audio in a specific language, you can do so by setting the language parameter in the query string. You can pass in any language code supported by Whisper through our language parameter. To learn more about languages, see Language.

https://api.deepgram.com/v1/listen?model=whisper&language=en

This is a list of Deepgram Features and their current status for use with Deepgram Whisper Cloud:

Feature Status
Alternatives ✅
Callbacks ✅
Speaker Diarization ✅
Entity Detection ❌
Find and Replace ✅
Keywords ❌
Language Detection ✅
Multichannel ✅
Numerals ✅
Paragraphs ✅
Profanity Filter ❌
Redaction ✅
Search ❌
Smart Format ✅
Summarization ✅
Topic Detection ✅
Utterances ✅
  • It’s important to understand that Whisper models are less scalable than all other Deepgram models due to their inherent model architecture. Deepgram’s non-Whisper models will return results faster and scale to a higher load, so we recommend using a Deepgram model such as Nova if it can meet your needs.
  • There is a 10 minute time out for all Deepgram models. Transcription requests that run longer than 10 minutes will return a 504 error.
  • Whisper models are not available on the EU endpoint. If you require EU data residency, use a Deepgram model such as Nova-3.

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