IP Library › Granted Patent US 12,664,442
Granted Patent B2
US 12,664,442 · App. 17/211,691 · Granted Jun 23, 2026

Computer-based techniques for capturing knowledge about computer-based tasks

Inventors: Fraser Anderson (Camrose, CA); George Fitzmaurice (Toronto, CA); Tovi Grossman (Toronto, CA); Rebecca Paige Krosnick (Ann Arbor, MI); Walter Lasecki (Ann Arbor, MI); Justin Frank Matejka (Newmarket, CA); Steve Oney (Ann Arbor, MI)
Assignee: AUTODESK, INC.
G06N5/02G06F3/167G06F9/451G10L15/1815G10L15/22G10L25/63G10L2015/088
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Quick Facts
Patent No.
US 12,664,442
App. No.
17/211,691
Filed
Mar 24, 2021
Granted
Jun 23, 2026
Kind
B2
Art Unit
2658
USPC
704/9
Abstract

In various embodiments, a knowledge capture application automatically captures knowledge associated with computer-based tasks. While a computer-based task is performed during a computer-based session, the knowledge capture application performs operation(s) on a user utterance to automatically generate a knowledge item. The knowledge capture application performs classification operation(s) on the knowledge item to generate a categorized knowledge item that associates the knowledge item with a first category. Subsequently, the knowledge capture application modifies a first element included in a graphical user interface to visually indicate an actual capture level associated with the first category. The knowledge capture application generates a knowledge dataset based on the first categorized knowledge item for storage or display. Advantageously, automatically generating the knowledge items and visually prompting the user via the actual capture levels during the computer-based session can increase both the comprehensiveness and the quality of the knowledge dataset.

Claims (47)

1 . A computer-implemented method for automatically capturing knowledge associated with computer-based tasks, the method comprising:

during a computer-based session during which a computer-based task is being performed, performing one or more operations on a first user utterance to automatically generate a first knowledge item;

performing one or more classification operations on the first knowledge item to generate a first categorized knowledge item that associates the first knowledge item with a first category;

modifying a first element included in a graphical user interface to visually indicate an actual capture level associated with the first category by updating a fill-level that graphically represents the actual capture level, wherein the first element further includes a target line that graphically represents a target capture level associated with the first category; and

generating a knowledge dataset based on the first categorized knowledge item for storage or display.

2 . The computer-implemented method of claim 1 , wherein performing the one or more operations on the first user utterance comprises executing a speech-to-text algorithm on the first user utterance to generate a transcribed utterance.

3 . The computer-implemented method of claim 1 , wherein the first category comprises one of an utterance category, a design intent category, a process category, a problem category, a to-do item category, or an important element category.

4 . The computer-implemented method of claim 1 , wherein the first element reflects the actual capture level instead of a previous capture level.

5 . The computer-implemented method of claim 1 , wherein performing the one or more classification operations on the first knowledge item comprises executing a natural language processing algorithm on the first knowledge item based on a sequence of one or more words that is indicative of the first category.

6 . The computer-implemented method of claim 1 , further comprising:

based on the first knowledge item, modifying a third element included in the graphical user interface to visually indicate a first overall actual capture level associated with the computer-based session;

performing one or more operations on a second user utterance to automatically generate a second knowledge item;

generating a second categorized knowledge item that associates the second knowledge item with a second category based on user input received via a second element included in the graphical user interface; and

based on the second knowledge item, modifying the third element to visually indicate a second overall actual capture level associated with the computer-based session instead of the first overall actual capture level.

7 . The computer-implemented method of claim 1 , further comprising modifying an output of the computer-based task based on the knowledge dataset to generate an annotated output that includes a description of at least a portion of the knowledge dataset.

8 . The computer-implemented method of claim 1 , wherein generating the knowledge dataset comprises:

aggregating the first categorized knowledge item with at least a second categorized knowledge item to generate a categorized knowledge list; and

aggregating the categorized knowledge list with at least one of a screen recording associated with the computer-based session, an audio recording that is associated with the computer-based session and includes the first user utterance, or software contextual data associated with the computer-based session to generate the knowledge dataset that is subsequently used to retrospectively review the computer-based session.

9 . The computer-implemented method of claim 8 , further comprising tracking at least one of commands associated with a software application, actions performed via a software application, events associated with a mouse, events associated with a keyboard, a cursor position, or a scrollbar position to generate the software contextual data.

10 . The computer-implemented method of claim 1 , wherein the first element comprises a first wedge associated with the first category, and the first wedge includes a shaded portion, wherein a top of the shaded portion corresponds to the fill-level that graphically represents the actual capture level.

11 . One or more non-transitory computer readable media including instructions that, when executed by one or more processors, cause the one or more processors to automatically capture knowledge associated with computer-based tasks by performing the steps of:

during a computer-based session during which a computer-based task is being performed, performing one or more operations on a first user utterance to automatically generate a first knowledge item;

performing one or more classification operations on the first knowledge item to generate a first categorized knowledge item that associates the first knowledge item with a first category;

modifying a first element included in a graphical user interface to visually indicate an actual capture level associated with the first category by updating a fill-level that graphically represents the actual capture level, wherein the first element further includes a target line that graphically represents a target capture level associated with the first category; and

generating a knowledge dataset based on the first categorized knowledge item for storage or display.

12 . The one or more non-transitory computer readable media of claim 11 ,

wherein performing the one or more operations on the first user utterance comprises:

transcribing the first user utterance to generate a first transcribed utterance;

determining a first emotion label based on the first user utterance; and

associating the first emotion label with the first transcribed utterance.

13 . The one or more non-transitory computer readable media of claim 11 , wherein the first category comprises one of an utterance category, a design intent category, a process category, a problem category, a to-do item category, or an important element category.

14 . The one or more non-transitory computer readable media of claim 11 , wherein the first element reflects the actual capture level instead of a previous capture level.

15 . The one or more non-transitory computer readable media of claim 11 , wherein performing the one or more classification operations on the first knowledge item comprises executing a classification algorithm on the first knowledge item based on at least one of a sequence of one or more words that is indicative of the first category, an emotion label associated with the first knowledge item, or software contextual data associated with the computer-based task.

16 . The one or more non-transitory computer readable media of claim 11 , further comprising modifying a second element included in the graphical user interface to visually indicate an overall capture level associated with the computer-based session.

17 . The one or more non-transitory computer readable media of claim 11 , wherein generating the knowledge dataset comprises:

aggregating the first categorized knowledge item with at least a second categorized knowledge item to generate a categorized knowledge list; and

aggregating the categorized knowledge list with at least one of a screen recording associated with the computer-based session, an audio recording that is associated with the computer-based session and includes the first user utterance, or software contextual data associated with the computer-based session to generate the knowledge dataset that is subsequently used to retrospectively review the computer-based session.

18 . The one or more non-transitory computer readable media of claim 11 , further comprising:

detecting a trigger based on at least one of the first user utterance or software contextual data associated with the computer-based session; and

in response, modifying the first element to visually prompt for a second user utterance that describes knowledge associated with the trigger.

19 . A system comprising:

one or more memories storing instructions; and

one or more processors coupled to the one or more memories that, when executing the instructions, perform the steps of:

during a computer-based session during which a computer-based task is being performed, performing one or more operations on a first user utterance to automatically generate a first knowledge item;

performing one or more classification operations on the first knowledge item to generate a first categorized knowledge item that associates the first knowledge item with a first category;

modifying a first element included in a graphical user interface to visually indicate an actual capture level associated with the first category by updating a fill-level that graphically represents the actual capture level, wherein the first element further includes a target line that graphically represents a target capture level associated with the first category; and

generating a knowledge dataset based on the first categorized knowledge item for storage or display.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 12, 2021
From: ANDERSON, FRASER; FITZMAURICE, GEORGE; GROSSMAN, TOVI; KROSNICK, REBECCA PAIGE; LASECKI, WALTER STEPHEN; MATEJKA, JUSTIN FRANK; ONEY, STEVE
To: AUTODESK, INC.
Reel/Frame 055900/0972 →
Continuity (2)
Provisional Application 63000680 · Mar 27, 2020
Related Publication 20210304019A1 · Sep 30, 2021
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