HTTP examples

These examples use the Deepgram Nova model; see the Speech-to-Text models for other models and endpoints.

Placeholders

The snippets below use these placeholders. Replace them before running the code.

Placeholder	Replace with
`SLNG_API_KEY`	An SLNG key from app.slng.ai/api-keys

Basic File Transcription

Upload an audio file (MP3, WAV, FLAC, OGG, M4A, or WebM) and get back the transcribed text. Here is a sample file you can use:

curl https://api.slng.ai/v1/stt/slng/deepgram/nova:3-en \
  -H "Authorization: Bearer SLNG_API_KEY" \
  -F "audio=@micro-machines.wav"

const formData = new FormData();
formData.append("audio", audioFile); // File from <input type="file">

const response = await fetch(
  "https://api.slng.ai/v1/stt/slng/deepgram/nova:3-en",
  {
    method: "POST",
    headers: {
      Authorization: "Bearer SLNG_API_KEY",
    },
    body: formData,
  },
);

const result = await response.json();
console.log("Transcription:", result.results.channels[0].alternatives[0].transcript);

import requests

url = "https://api.slng.ai/v1/stt/slng/deepgram/nova:3-en"
headers = {"Authorization": "Bearer SLNG_API_KEY"}

with open("micro-machines.wav", "rb") as audio_file:
    response = requests.post(url, headers=headers, files={"audio": audio_file})

result = response.json()
print("Transcription:", result["results"]["channels"][0]["alternatives"][0]["transcript"])

You should get a response like this:

{
  "metadata": {
    "request_id": "e5fed572-6eac-4b70-81f3-21ba1641dd12",
    "duration": 29.888374,
    "channels": 1,
    "model_info": {
      "1abfe86b-e047-4eed-858a-35e5625b41ee": {
        "name": "2-general-nova",
        "version": "2024-01-06.5664",
        "arch": "nova-2"
      }
    }
  },
  "results": {
    "channels": [
      {
        "alternatives": [
          {
            "transcript": "is the micro machine man presenting the most midget miniature motocator of micro machine...",
            "confidence": 0.9823751,
            "words": [
              { "word": "is", "start": 0.16, "end": 0.32, "confidence": 0.998 },
              { "word": "the", "start": 0.32, "end": 0.40, "confidence": 0.613 },
              { "word": "micro", "start": 0.40, "end": 0.64, "confidence": 0.727 },
              ...
            ]
          }
        ]
      }
    ]
  }
}

Going further

You can pass additional form fields to customize the transcription:

Language: If you know the language, pass language=en (or es, fr, etc.). Not all models auto-detect, so setting this explicitly can improve accuracy.
Diarization: Pass diarize=true to identify different speakers in a multi-speaker recording. The response will include a speaker field on each word. PLease check the models documentation for specific diarization config.
Punctuation: Pass punctuate=true to add punctuation to the transcript automatically.

For the full parameter list per model, see the Speech-to-Text API reference.

Next Steps

Live STT demo

Try real-time speech recognition in your browser, no setup needed

STT WebSocket examples

Real-time transcription as users speak

Speech-to-Text models

Browse all STT models and endpoints

STT API reference

Endpoint-specific parameters

Get started

Text-to-Speech

Speech-to-Text

Managed Agents

Integrations

SDKs & Tools

Reference

Placeholders

Basic File Transcription

Going further

Next Steps

Live STT demo

STT WebSocket examples

Speech-to-Text models

STT API reference

​Placeholders

​Basic File Transcription

​Going further

​Next Steps

Live STT demo

STT WebSocket examples

Speech-to-Text models

STT API reference

Placeholders

Basic File Transcription

Going further

Next Steps