Detecting and assigning action items to conversation participants in real-time and detecting completion thereof
Described herein is a system for automatically detecting and assigning action items in a real-time conversation and determining whether such action items have been completed. The system detects, during a meeting, a plurality of action items and an utterance that corresponds to a completed action item. Responsive to detecting the utterance, the system generates a similarity score with respect to a first action item of the plurality of action items. The system compares the similarity score to a first threshold. Responsive to determining that the similarity score does not exceed the first threshold, the system generates a second similarity score with respect to a second action item of the plurality of action items. The system compares the second similarity score to a second threshold, which exceeds the first threshold. Responsive to determining that the second similarity score exceeds the second threshold, the system marks the second action item as completed.
1 . A non-transitory computer readable storage medium comprising stored instructions, the instructions when executed by one or more processors cause the one or more processors to:
detect, during a meeting, that an utterance corresponds to a completed action item;
for each respective action item of a plurality of open action items satisfying a context, generate a respective similarity score;
identify a matching action item of the open plurality of action items based on its respective similarity score; and
mark, in response to identifying the matching action item based on its respective similarity score, the matching action item completed.
2 . The non-transitory computer readable storage medium of claim 1 , wherein a first similarity score is generated for a first action item, and wherein a second similarity score is generated for a second action item responsive to determining that the first similarity score does not exceed a threshold.
3 . The non-transitory computer readable storage medium of claim 2 , wherein the second action item is selected to be a part of the plurality of open action items based on it being next in a group of candidate action items for having a next most recent timestamp from the meeting relative to the first action item.
4 . The non-transitory computer readable storage medium of claim 1 , wherein the plurality of open action items are detected within a threshold amount of time from a current time.
5 . The non-transitory computer readable storage medium of claim 1 , wherein the instructions further cause the one or more processors to:
receive, from an administrator, a threshold number and threshold amount of time;
determine a subset of the plurality of action items, wherein the subset includes fewer than the threshold number of action items and each action item of the subset occurred within a threshold amount of time from a time that the utterance was detected; and
generate similarity scores for action items in the subset based on recency of the action items.
6 . The non-transitory computer readable storage medium of claim 1 , wherein the instructions further cause the one or more processors to:
transmit a notification, via a user interface at a client device, to an owner of the matching action item that the action item has been completed.
7 . The non-transitory computer readable storage medium of claim 1 , wherein each similarity score is generated using a machine learning model, the machine learning model trained on a plurality of pairings of action items and utterances, wherein each pairing is labeled with a similarity score.
8 . The non-transitory computer readable storage medium of claim 1 , wherein each similarity score is generated using fuzzy logic.
9 . A method comprising:
detecting, during a meeting, that an utterance corresponds to a completed action item;
for each respective action item of a plurality of open action items satisfying a context, generating a respective similarity score;
identifying a matching action item of the plurality of open action items based on its respective similarity score; and
marking, in response to identifying the matching action item based on its respective similarity score, the matching action item completed.
10 . The method of claim 9 , wherein a first similarity score is generated for a first action item, and wherein a second similarity score is generated for a second action item responsive to determining that the first similarity score does not exceed a threshold.
11 . The method of claim 10 , wherein the second action item is selected to be a part of the plurality of open action items based on it being next in a group of candidate action items for having a next most recent timestamp from the meeting relative to the first action item.
12 . The method of claim 9 , wherein each of the plurality of open action items are detected within a threshold amount of time from a current time.
13 . The method of claim 9 , further comprising:
receiving, from an administrator, a threshold number and threshold amount of time;
determining a subset of the plurality of action items, wherein the subset includes fewer than the threshold number of action items and each action item of the subset occurred within a threshold amount of time from a time that the utterance was detected; and
generating similarity scores for action items in the subset based on recency of the action items.
14 . The method of claim 9 , further comprising transmitting a notification, via a user interface at a client device, to an owner of the matching action item that the action item has been completed.
15 . The method of claim 9 , wherein each similarity score is generated using a machine learning model, the machine learning model trained on a plurality of pairings of action items and utterances, wherein each pairing is labeled with a similarity score.
16 . The method of claim 9 , wherein each similarity score is generated using fuzzy logic.
17 . A system comprising:
memory with instructions encoded thereon; and
one or more processors that, when executing the instructions, are caused to perform operations comprising:
detecting, during a meeting, that an utterance corresponds to a completed action item;
for each respective action item of a plurality of open action items satisfying a context, generating a respective similarity score;
identifying a matching action item of the plurality of open action items based on its respective similarity score; and
marking, in response to identifying the matching action item based on its respective similarity score, the matching action item completed.
18 . The system of claim 17 , wherein a first similarity score is generated for a first action item, and wherein a second similarity score is generated for a second action item responsive to determining that the first similarity score does not exceed a threshold.
19 . The system of claim 18 , wherein the second action item is selected to be a part of the plurality of open action items based on it being next in a group of candidate action items for having a next most recent timestamp from the meeting relative to the first action item.
20 . The system of claim 17 , wherein each of the plurality of open action items are detected within a threshold amount of time from a current time.