Auto Chapters
The Auto Chapters model summarizes audio data over time into chapters. Chapters makes it easy for users to navigate and find specific information.
Each chapter contains the following:
- Summary
- One-line gist
- Headline
- Start and end timestamps
Auto Chapters and Summarization
You can only enable one of the Auto Chapters and Summarization models in the same transcription.
Quickstart
Python
TypeScript
Go
Java
C#
Ruby
Example output
Auto Chapters Using LeMUR
Check out this cookbook Creating Chapter Summaries for an example of how to leverage LeMUR’s custom text input parameter for chapter summaries.
API reference
Request
Response
The response also includes the request parameters used to generate the transcript.
Frequently asked questions
Can I specify the number of chapters to be generated by the Auto Chapters model?
No, the number of chapters generated by the Auto Chapters model isn’t configurable by the user. The model automatically segments the audio file into logical chapters as the topic of conversation changes.
Troubleshooting
Why am I not getting any chapter predictions for my audio file?
One possible reason is that the audio file doesn’t contain enough variety in topic or tone for the model to identify separate chapters. Another reason could be due to background noise or low-quality audio interfering with the model’s analysis.