The list of topics that were predicted for the audio file, including the text that influenced each topic label prediction, and other metadata about relevancy and timestamps.
Will be either "success", or "unavailable" in the rare case that the Topic Detection model failed.
For each unique topic label detected in the results array, the summary key will show the relevancy for that label across the entire audio file. For example, if the Science>Environment label is detected only 1 time in a 60 minute audio file, the summary key will show a low relevancy score for that label, since the entire transcription was not found to consistently be about Science>Environment.
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With Topic Detection, AssemblyAI can label the topics that are spoken in your audio/video files. The predicted topic labels follow the standardized IAB Taxonomy, which makes them suitable for Contextual Targeting use cases. The below table shows the 698 potential topics the API can predict.
Simply include the
iab_categoriesparameter in yourPOSTrequest when submitting audio files for transcription, and set this parameter totrue, as shown in the cURL request on the right.Once the transcription is complete, and you get the transcription result, there will be an additional key
iab_categories_resultin the JSON response. Below, we drill into that key and what data it includes.