Generating and providing in-meeting coaching for video calls
The present disclosure is directed toward systems, methods, and non-transitory computer readable media for generating and providing intelligent insights for video calls and other virtual meetings. In some embodiments, the disclosed systems analyze stored meeting data from past video calls and other virtual meetings to generate intelligent insights for an upcoming video call. The disclosed systems also generate and provide intelligent insights or coaching tools for ongoing video calls. As part of the intelligent coaching tools for ongoing video calls, the disclosed systems can generate predictions for accomplishing target goals for the video calls. Further, the disclosed systems can generate intelligent insights or coaching tools after video calls take place.
1 . A method comprising:
generating, from video call data extracted from past video calls associated with a user account of a content management system, a knowledge graph defining relationships between content items stored for the user account;
detecting, from video call data of an ongoing video call, a plurality of discussion topics, wherein each discussion topic comprises subject matter discussed between participants of the ongoing video call;
selecting, using a topic prediction model, a discussion topic of the plurality of discussion topics according to contemporaneous video call data of the video call data;
performing, during the ongoing video call, a continuous semantic search of the knowledge graph to identify content items corresponding to the discussion topic by:
based on detecting the discussion topic, identifying via the continuous semantic search a first node of the knowledge graph corresponding to the discussion topic; and
identifying, via the continuous semantic search, nodes of the knowledge graph that are within a threshold distance of the first node corresponding to the discussion topic; and
determining, from the continuous semantic search of the knowledge graph, a second node of the nodes that corresponds to a content item stored for the user account to recommend for sharing within the ongoing video call.
2 . The method of claim 1 , wherein performing the continuous semantic search comprises analyzing the knowledge graph during the ongoing video call by:
identifying, within the knowledge graph, a first node representing the ongoing video call corresponding to the discussion topic; and
determining, from the first node, distances of additional nodes representing content items stored for the user account based on topics associated with the content items.
3 . The method of claim 1 , wherein determining the content item to recommend comprises determining, from among a plurality of content items stored for the user account within the content management system, a content item whose node within the knowledge graph has a shortest distance to a node representing the discussion topic.
4 . The method of claim 1 , further comprising:
determining a tone associated with the ongoing video call; and
generating, for display on a client device of the user account during the ongoing video call, a suggested phrase for the discussion topic according to the tone.
5 . The method of claim 1 , wherein:
detecting an incorrect statement made during the ongoing video call; and
generating, for display on a client device of the user account during the ongoing video call, a suggested phrase for correcting the incorrect statement.
6 . The method of claim 1 , further comprising:
determining a target topic from analysis of an agenda associated with the ongoing video call;
detecting divergence from the target topic based on the video call data of the ongoing video call; and
generating, for display on a client device of the user account during the ongoing video call, a suggested phrase for returning to the target topic.
7 . The method of claim 1 , further comprising:
analyzing a plurality of content items stored for the user account within the content management system;
generating, from the plurality of content items stored for the user account, a suggested phrase corresponding to the discussion topic of the ongoing video call; and
providing the suggested phrase for display on a client device associated with the user account during the ongoing video call.
8 . A system comprising:
at least one processor; and
a non-transitory computer readable medium comprising instructions that, when executed by the at least one processor, cause the system to:
generate, from video call data extracted from past video calls associated with a user account of a content management system, a knowledge graph defining relationships between content items stored for the user account;
detect, from video call data of an ongoing video call, a plurality of discussion topics, wherein each discussion topic comprises subject matter discussed between participants of the ongoing video call;
select, using a topic prediction model, a discussion topic of the plurality of discussion topics according to contemporaneous video call data of the video call data;
perform, during the ongoing video call, a continuous semantic search of the knowledge graph to identify content items corresponding to the discussion topic by:
based on detecting the discussion topic, identifying via the continuous semantic search a first node of the knowledge graph corresponding to the discussion topic; and
identifying, via the continuous semantic search, nodes of the knowledge graph that are within a threshold distance of the first node corresponding to the discussion topic;
determine, from the continuous semantic search of the knowledge graph, a second node of the nodes that corresponds to a content item stored for the user account; and
generating, for display on a client device associated with the user account during the ongoing video call, a recommendation for sharing the content item within the ongoing video call.
9 . The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to generate the knowledge graph by:
determining topics for a plurality of content items stored for the user account within the content management system;
determining topics from the video call data extracted from the past video calls; and
generating, from the topics of the video call data and the topics of the plurality of content items, edges representing relationships between nodes corresponding to the past video calls and the plurality of content items.
10 . The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to determine the content item to recommend by:
determining, from the knowledge graph, a plurality of content items stored for the user account corresponding to the discussion topic;
ranking the plurality of content items according to confidence values for corresponding to the discussion topic; and
selecting the content item based on ranking the plurality of content items according to the confidence values.
11 . The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to:
detect, based on changes in the video call data of the ongoing video call, a new discussion topic discussed between participants of the ongoing video call;
update the continuous semantic search to analyze the knowledge graph based on the new discussion topic; and
determine, for display on the client device based on updating the continuous semantic search, a new content item stored for the user account and corresponding to the new discussion topic.
12 . The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to:
receive, from the client device during the ongoing video call, an indication of selecting the recommendation to share the content item; and
in response to the indication, generate a sharing notification for display on client devices associated with other participants, wherein the sharing notification is selectable to provide the content item to a corresponding user account within the content management system.
13 . The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to:
analyze a plurality of content items within the content management system and accessible by each user account participating in the ongoing video call;
generate, from the plurality of content items accessible by each user account, a suggested phrase corresponding to the discussion topic of the ongoing video call; and
provide the suggested phrase for display on a client device associated with the user account during the ongoing video call.
14 . The system of claim 8 , further comprising instructions that, when executed by the at least one processor, cause the system to:
determine, from the video call data of the ongoing video call, an effectiveness score indicating a measure of communication effectiveness for the user account; and
generating, for display on the client device of the user account during the ongoing video call, a notification comprising a suggestion for improving the effectiveness score.
15 . A non-transitory computer readable medium comprising instructions that, when executed by at least one processor, cause the at least one processor to:
generate, from video call data extracted from past video calls associated with a user account of a content management system, a knowledge graph defining relationships between content items stored for the user account;
detect, from video call data of an ongoing video call, a plurality of discussion topics, wherein each discussion topic comprises subject matter discussed between participants of the ongoing video call;
select, using a topic prediction model, a discussion topic of the plurality of discussion topics according to contemporaneous video call data of the video call data;
perform, during the ongoing video call, a continuous semantic search of the knowledge graph by continually searching content items stored for the user account during the ongoing video call to identify content items corresponding to the discussion topic by:
based on detecting the discussion topic, identifying via the continuous semantic search a first node of the knowledge graph corresponding to the discussion topic; and
identifying, via the continuous semantic search, nodes of the knowledge graph that are within a threshold distance of the first node corresponding to the discussion topic; and
determine, from the continuous semantic search of the knowledge graph, a second node of the nodes that corresponds to a content item stored for the user account to recommend for sharing within the ongoing video call.
16 . The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the at least one processor to generate the knowledge graph by:
determining user account interactions for a plurality of content items accessed during the past video calls and stored for the user account within the content management system; and
generating, from the user account interactions, nodes representing the plurality of content items and edges representing relationships between the plurality of content items.
17 . The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the at least one processor to analyze the knowledge graph during the ongoing video call by:
identifying, within the knowledge graph, a first node representing the discussion topic; and
determining, from the first node, distances of additional nodes representing content items stored for the user account.
18 . The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the at least one processor to:
determine a target topic using natural language processing for an agenda associated with the ongoing video call;
detect divergence from the target topic based on the video call data of the ongoing video call; and
generate, for display on a client device of the user account during the ongoing video call, a suggested phrase prompting a return to the target topic.
19 . The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the at least one processor to:
generate, from the content item determined from the continuous semantic search, a suggested phrase corresponding to the discussion topic of the ongoing video call; and
provide the suggested phrase for display on a client device associated with the user account during the ongoing video call.
20 . The non-transitory computer readable medium of claim 15 , further comprising instructions that, when executed by the at least one processor, cause the at least one processor to:
determine, from the video call data indicating vocabulary used by the user account during the ongoing video call, an effectiveness score indicating a measure of communication effectiveness for the user account; and
generate, for display on a client device of the user account during the ongoing video call, a notification comprising a suggestion for changing the vocabulary to improve the effectiveness score.