Systems and methods for automatically generating conversation outlines and annotation summaries

A computing system for presenting a conversation, the computing system comprising:

• one or more processors;
• and
• a memory storing instructions that, upon execution by the one or more processors, cause the computing system to perform one or more processes comprising:
• obtaining, via a virtual participant, a set of audio data associated with a conversation while the conversation occurs;
• transcribing, via the virtual participant, the set of audio data into a set of text data while the conversation occurs;
• obtaining a set of annotations associated with the set of text data while the conversation occurs;
• identifying one or more topic transitions based at least in part upon the set of text data;
• generating a plurality of headings for a plurality of conversation topics based at least in part on the set of text data and the one or more topic transitions, the generating a plurality of headings including applying a machine learning model to the set of text data to generate at least one of the plurality of headings;
• generating a conversation summary including the plurality of headings based at least in part upon the one or more topic transitions;
• obtaining a set of visual data associated with the conversation, each visual data of the set of visual data corresponding to a timestamp;
• and
• presenting the set of annotations, the conversation summary, and the set of visual data embedded in the set of text data to a group of actual participants.

A non-transitory computer-readable medium storing instructions for presenting a conversation, the instructions upon execution by one or more processors of a computing system, cause the computing system to perform one or more processes including:

• obtaining, via a virtual participant, a set of audio data associated with a conversation while the conversation occurs;
• transcribing, via the virtual participant, the set of audio data into a set of text data while the conversation occurs;
• obtaining a set of annotations associated with the set of text data while the conversation occurs;
• identifying one or more topic transitions based at least in part upon the set of text data;
• generating a plurality of headings for a plurality of conversation topics based at least in part on the set of text data and the one or more topic transitions, the generating a plurality of headings comprising applying a machine learning model to the set of text data to generate at least one of the plurality of headings;
• generating a conversation summary including the plurality of headings based at least in part upon the one or more topic transitions;
• obtaining a set of visual data associated with the conversation, each visual data of the set of visual data corresponding to a timestamp;
• and
• presenting the set of annotations, the conversation summary, and the set of visual data embedded in the set of text data to a group of actual participants.

A computer-implemented method for presenting a conversation, the method comprising:

• obtaining, via a virtual participant, a set of audio data associated with a conversation while the conversation occurs;
• transcribing, via the virtual participant, the set of audio data into a set of text data while the conversation occurs;
• obtaining a set of annotations associated with the set of text data while the conversation occurs;
• identifying one or more topic transitions based at least in part upon the set of text data;
• generating a plurality of headings for a plurality of conversation topics based at least in part on the set of text data and the one or more topic transitions by applying a machine learning model to the set of text data;
• generating a conversation summary based at least in part upon the one or more topic transitions, the conversation summary including the plurality of headings;
• obtaining a set of visual data associated with the conversation, each visual data of the set of visual data corresponding to a timestamp;
• and
• presenting the set of annotations, the conversation summary, and the set of visual data embedded in the set of text data to a group of actual participants.