New Summarization Models Tailored to Use Cases

Lee Vaughn -

We are excited to announce that new Summarization models are now available! Developers can now choose between multiple summary models that best fit their use case and customize the output based on the summary length.

The new models are:

  • Informative which is best for files with a single speaker, like a presentation or lecture
  • Conversational which is best for any multi-person conversation, like customer/agent phone calls or interview/interviewee calls
  • Catchy which is best for creating video, podcast, or media titles

Developers can use the summary_model parameter in their POST request to specify which of our summary models they would like to use. This new parameter can be used along with the existing summary_type parameter to allow the developer to customize the summary to their needs.

import requests
endpoint = "https://api.assemblyai.com/v2/transcript"
json = {
    "audio_url": "https://bit.ly/3qDXLG8",
    "summarization": True,
    "summary_model": "informative", # conversational | catchy
    "summary_type": "bullets" # bullets_verbose | gist | headline | paragraph
}
headers = {
	"authorization": "YOUR-API-TOKEN",
    "content-type": "application/json"
}
response = requests.post(endpoint, json=json, headers=headers)
print(response.json())

Check out our latest blog post to learn more about the new Summarization models or head to the AssemblyAI Playground to test Summarization in your browser!