Entity Detection

When Entity Detection is enabled, the Punctuation feature will be enabled by default.

Enable Feature

To enable Entity Detection, when you call Deepgram’s API, add a detect_entities parameter set to true in the query string:

detect_entities=true&punctuate=true

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When Entity Detection is enabled, Punctuation will also be enabled by default.

To transcribe audio from a file on your computer, run the following curl command in a terminal or your favorite API client.

curl \
  --request POST \
  --header 'Authorization: Token YOUR_DEEPGRAM_API_KEY' \
  --header 'Content-Type: audio/wav' \
  --data-binary @youraudio.wav \
  --url 'https://api.deepgram.com/v1/listen?detect_entities=true&punctuate=true'

Replace YOUR_DEEPGRAM_API_KEY with your Deepgram API Key.

Analyze Response

When the file is finished processing (often after only a few seconds), you’ll receive a JSON response that has the following basic structure:

{
  "metadata": {
    "transaction_key": "string",
    "request_id": "string",
    "sha256": "string",
    "created": "string",
    "duration": 0,
    "channels": 0
  },
  "results": {
    "channels": [
      {
        "alternatives":[],
      }
    ]
  }

Let's look more closely at the alternatives object:

"alternatives":[
  {
    "transcript":"Welcome to the Ai show. I'm Scott Stephenson, cofounder of Deepgram...",
    "confidence":0.9816771,
    "words": [...],
    "entities":[
      {
        "label":"NAME",
        "value":" Scott Stephenson",
        "confidence":0.9999924,
        "start_word":6,
        "end_word":8
      },
      {
        "label":"ORG",
        "value":" Deepgram",
        "confidence":0.9999757,
        "start_word":10,
        "end_word":11
      },
      {
        "label": "CARDINAL_NUM",
        "value": "one",
        "confidence": 1,
        "start_word": 186,
        "end_word": 187
      },
      ...
    ]
  }
]

In this response, we see that each alternative contains:

• transcript: Transcript for the audio being processed.
• confidence: Floating point value between 0 and 1 that indicates overall transcript reliability. Larger values indicate higher confidence.
• words: Object containing each word in the transcript, along with its start time and end time (in seconds) from the beginning of the audio stream, and a confidence value.
• entities: Object containing the information about entities for the audio being processed.

And we see that each entities object contains:

• label: Type of entity identified.
• value: Text of entity identified.
• confidence: Floating point value between 0 and 1 that indicates entity reliability. Larger values indicate higher confidence.
• start_word: Location of the first character of the first word in the section of audio being inspected for entities.
• end_word: Location of the first character of the last word in the section of audio being inspected for entities.

By default, Deepgram applies its base tier, general AI model, which is a good, general-purpose model for everyday situations. To learn more about the customization possible with Deepgram's API, check out the Deepgram API Reference.

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All entities are available in English.

Identifiable Entities

Entities that our API can identify include the following:

Use Cases

Some examples of uses for Entity Detection include:

• Customers who want to improve Conversational AI and Voice Assistant by triggering particular workflows and responses based on identified name, address, location, and other key entities.
• Customers who want to enhance customer service and user experience by extracting meaningful and relevant information about key entities such as a person, organization, email, and phone number.
• Customers who want to derive meaningful and actionable insights from the audio data based on identified entities in conversations.