Understanding Video Podcasts
Feel free to look through the colab link above to get a sense of how to use the VLM-1 API to extract structured data from video podcasts and interviews.
In the sections below, we’ll showcase a few notable features of the API for analyzing podcasts or video interviews. You can also refer to the features extracted in the Analyzing Audio Podcasts guide for a more detailed overview of the audio transcription capabilities of the API.
VLM-1 can automatically generate chapter summaries for video podcasts or interviews. This can be useful for creating a table of contents for the video, or for generating a summary of the key points discussed in the video. As you can see in the sample output below, the API is able to extract a general visual description of the segment with timestamps, the highlighted chapter text (“AI Will Create More Successful Founders”), and different persons/objects in the scene that may be relevant for analysis.
VLM-1 can also extract text from slides or visual aids that are shown during the video. This can be useful for extracting key points, quotes, or other information that is presented visually in the video. As you can see in the sample output below, the API is able to extract the highlighted text from right portion of the screen (“Get In Early”) alongside all the other chapter texts displayed.
