Detecting and assigning action items to conversation participants in real-time and detecting completion thereof

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, a plurality of action items;

detect, during the meeting, an utterance that corresponds to a completed action item;

generate, in response to a determination of the utterance, first a similarity score with respect to a first action item of the plurality of action items;

compare the first similarity score to a first threshold;

generate, in response a determination that the first similarity score does not exceed the first threshold, a second similarity score with respect to a second action item of the plurality of action items;

compare the second similarity score to a second threshold, the second threshold exceeding the first threshold; and

mark, in response to a determination that the second similarity score exceeds the second threshold, the second action item completed.

2. The non-transitory computer readable storage medium of claim 1 , wherein the first action item is a most recently uttered action item, wherein the second action item is a next most recently uttered action item with respect to the most recently uttered action item, and wherein the second threshold is weighted based on an amount of time that has passed since the next most recently uttered action item was uttered.

3. The non-transitory computer readable storage medium of claim 1 , wherein the instructions to detect, during a meeting, the plurality of action items, further cause the one or more processors to detect each of the plurality of action items within a threshold amount of time from a current time.

4. 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.

5. The non-transitory computer readable storage medium of claim 1 , wherein the instructions to generate the first similarity score further cause the one or more processors to generate the first similarity score based on cosine similarity between vectors that represent the first action item and the completed action item.

6. The non-transitory computer readable storage medium of claim 5 , wherein the vectors are created using word embeddings.

7. 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 second action item that the action item has been completed.

8. The non-transitory computer readable storage medium of claim 1 , wherein the first 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.

9. The non-transitory computer readable storage medium of claim 1 , wherein the first similarity scores is generated using fuzzy logic.

10. The non-transitory computer readable storage medium of claim 1 , wherein the instructions further cause the one or more processors to:

rank the first action item higher in a ranking of the plurality of action items, the ranking determined based on a recency of when the action items were detected.

11. A method for closing completed action items during a meeting, the method comprising:

detecting, during a meeting, a plurality of action items;

detecting, during the meeting, an utterance that corresponds to a completed action item;

generating, in response to detection of the utterance, a first similarity score with respect to a first action item of the plurality of action items;

comparing the first similarity score to a first threshold;

generating, in response to a determination that the first similarity score does not exceed the first threshold, a second similarity score with respect to a second action item of the plurality of action items;

comparing the second similarity score to a second threshold, the second threshold exceeding the first threshold; and

marking, in response to a determination that the second similarity score exceeds the second threshold, the second action item completed.

12. The method of claim 11 , wherein the first action item is a most recently uttered action item, wherein the second action item is a next most recently uttered action item with respect to the most recently uttered action item, and wherein the second threshold is weighted based on an amount of time that has passed since the next most recently uttered action item was uttered.

13. The method of claim 11 , wherein detecting, during a meeting, each of the plurality of action items further comprises detecting each of the plurality of action items within a threshold amount of time from a current time.

14. The method of claim 11 , 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.

15. The method of claim 11 , wherein generating the first similarity score further comprises generating the first similarity score based on cosine similarity between vectors representing the first action item and the completed action item.

16. The method of claim 15 , wherein the vectors are created using word embeddings.

17. The method of claim 11 , further comprising:

transmitting a notification, via a user interface at a client device, to an owner of the second action item that the action item has been completed.

18. The method of claim 11 , wherein the first 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.

19. The method of claim 11 , wherein the first similarity score is generated using fuzzy logic.

20. A system for closing completed action items during a meeting, the system comprising:

a first detection module for detecting, during a meeting, a plurality of action items;

a second detection module for detecting, during the meeting, an utterance that corresponds to a completed action item;

a similarity score generation module for:

generating, in response to a detection of the utterance, a first similarity score with respect to a first action item of the plurality of action items;

comparing the first similarity score to a first threshold;

generating, in response to a determination that the first similarity score does not exceed the first threshold, a second similarity score with respect to a second action item of the plurality of action items; and

comparing the second similarity score to a second threshold, the second threshold exceeding the first threshold; and

an action item completion module for marking, in response to a determination that the second similarity score exceeds the second threshold, the second action item completed.