Summarizing virtual meetings
In this guide, we'll show you how to use the Summarization model to automatically generate summaries of your virtual meetings, so you can quickly review important information and take action based on the insights gathered from the conversations.
Create a new file and import the necessary libraries for making an HTTP request.
Set up the API endpoint and headers. The headers should include your API token.
Upload your local file to the AssemblyAI API.
We delete uploaded files from our servers either after the transcription has completed, or 24 hours after you uploaded the file. After the file has been deleted, the corresponding
upload_urlis no longer valid.
upload_urlreturned by the AssemblyAI API to create a JSON payload containing the
To use the Summarization model, set
True. By default, the
You can find all possible summary models and types here. Note that if the
summary_typeis also a required parameter, and vice versa.
POSTrequest to the AssemblyAI API endpoint with the payload and headers.
After making the request, you'll receive an ID for the transcription. Use it to poll the API every few seconds to check the status of the transcript job. Once the status is
completed, you can retrieve the transcript from the API response, using the
summarykey to view the result of the summarization.
Understanding the response
Your transcript summary is located in the
summary key of the API response. In addition to standard transcript metadata, you'll also find other parameters containing the
summary_type, which indicates the type of summary that was generated, and
summary_model, which indicates the specific AI summarization model that was used to generate the summary. More information on these parameters and their possible values can be found below.
Refer to the API reference for a breakdown of every element in your transcript output.
Identify the most important information you want to include in the summary and choose the Summarization model and type that best suits your use case.
When using the
conversational model, make sure that the two speakers have distinct voices and that there's minimal background noise.
For shorter recordings, the
headline options may provide the most effective summary, whereas for longer recordings, the
paragraph options may be more appropriate.
Consider the context in which the summary will be used, and whether additional context or explanation is necessary to understand the summary.
Experiment with different summarization options to find the one that works best for your specific use case.
AssemblyAI maintains a number of different summarization models for different use cases, so you can choose between a more informative summary or a catchier tagline for your audio. You can refer to the AssemblyAI blog to see more examples of our summarization features in action.
If you're experiencing issues with generating a summary, make sure that you've included the
summarization parameter in your request and set it to
true. In addition, note that the Auto Chapters model and the Summarization model can't be active in the same request. If you try to enable both Auto Chapters and Summarization in a single request, you'll receive the following error message:
"Only one of the following models can be enabled at a time: auto_chapters, summarization."