Generating summary and next actions in real-time for multiple users from interaction records in natural language

Abstract

A system receives messaging, video and/or audio input streams including dialogue spoken by users at a group meeting. From these inputs, the system obtains single or multiple interaction records including natural language text memorializing content spoken by each speaker at a meeting, analyzes the content, and identifies single or multiple action item tasks in the interaction records. The system then generates summaries indicating the action item tasks for the users. From the dialogue content, the system further detects whether each action item is addressed, and whether the action item for a user has a solution, or not. The system further detects whether one action item is a precondition for resolving another action item by the user or in conjunction with another user. Using a pre-configured template, the system generates action item summaries, any associated solution, and any relationship or precondition between action items and presents the summary to a user.