Abstract: One method for multimodal meeting segmentation includes receiving a meeting recording and a transcript, the meeting recording comprising a first media stream; generating, using a trained machine learning (“ML”) model, a first set of embeddings corresponding to the first media stream and a second set of embeddings corresponding to the transcript; generating a first set of segments based on the first set of embeddings and a second set of segments based on the second set of embeddings; generating a final set of segments based on the first and second sets of segments; and associating the final set of segments with the meeting recording and storing the final set of segments.

Abstract: Example methods and systems facilitate user actions during a chat session on an online chat platform. A client device is installed with a chat and video conference application. The chat and video conference application includes a machine learning (ML) model. The client device receives a chat message during a chat session and identifies an action item from the chat message using the ML model. One or more GUI elements can be generated associated with a functionality of an application corresponding to the action item. A GUI element can be activated to invoke the functionality of the application.