Topic Detection

topics boolean   Default: false

Deepgram’s Topic Detection feature identifies key topics within the transcript, returning a list of text segments and the topics found within each segment.

The list of topics that can be identified is not a fixed list; this TSLM powered feature is able to generate topics based on the context of the language content in the transcript. You may also choose to use the optional custom-topic parameter to provide a custom topic you want detected if present within your audio.

Enable Feature

To enable Topic Detection, use the following parameter in the query string when you call Deepgram’s /listen endpoint:

topics=true

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?topics=true'

Query Parameters

Analyze Response

When the file is finished processing, you’ll receive a JSON response that has the following basic structure:

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{
2
  "metadata": {...},
3
  "results": {
4
    "channels": [
5
      {
6
        "alternatives": [...]
7
      }
8
    ],
9
    "topics": {
10
      "segments": [
11
        {
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          "text": "Can I upgrade my phone?",
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          "start_word": 13,
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          "end_word": 17,
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          "topics": [
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            { "topic": "Phone upgrade", "confidence_score": 0.9661531 }
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          ]
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        }
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      ]
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    }
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  }
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}

The response object values for topics are:

• segments: The list of segments of text identified by the model as containing notable topics.
• topic: The name of the topic detected by the model.
• confidence_score: a floating point from 0 to 1 representing the models confidence in this prediction.

API Warning Response

Warning

If you request Topic Detection with an unsupported language by specifying a language code such as topics=true&language=es or topics=true&detect_language=true where the detected language is unsupported, you will get the warning message below.

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"warnings": [
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  {
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    "parameter": "topics",
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    "type": "unsupported_language",
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    "message": "Topics is only supported for English."
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  }
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]

Example Warning

Here is an example of the JSON structure of a request with warning object.

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{
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 "metadata": {
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...
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       },
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     "warnings": [
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       {
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         "parameter": "topic",
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         "type": "unsupported_language",
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         "message": "Topics is only supported for English."
10
       }
11
     ]
12
   },
13
 "results": {
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       "channels": [
15
            {
16
                "alternatives": [...]
17
            }
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        ], 
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    }
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}

Use Cases

Some examples of uses for Topic Detection include:

• Customers who want to help their Quality Assurance team analyze conversations to identify trends and patterns based on discussed topics.
• Customers who need to extract meaningful and actionable insights from conversations and audio data based on discussed topics.
• Customers who want to enhance search capabilities by tagging conversations based on identified topics.