Granted Patent B2

US 12,248,757 · App. 18/184,852 · Granted Mar 11, 2025

Inventors: Natalia Russi-Vigoya (Round Rock, TX); Jennifer M. Hatfield (San Francisco, CA); Jill S. Dhillon (Jupiter, FL); Juhi Bharat (Highland Park, NJ); Joshua Totte (Santa Monica, CA)

Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION

G06F40/42G06F40/166

Abstract

Claims (63)

1. A computer-based method of supporting neurodivergent comprehension of content comprising:

retrieving responses to a questionnaire, the retrieved responses including a series of reading preferences and behaviors associated with a registered user;

receiving an activation command from the registered user;

automatically identifying, within displayed content, predicted difficult comprehension areas using a pre-trained natural language processing model based on the series of reading preferences and behaviors associated with the registered user;

marking a textual element associated with the predicted difficult comprehension areas that may be transformed to improve comprehensibility of the predicted difficult comprehension areas for the registered user;

detecting user interaction with the marked textual element;

in response to detecting user interaction with the marked textual element, transforming the marked textual element to address the predicted difficult comprehension areas based on the series of reading preferences and behaviors associated with the registered user;

in response to transforming the marked textual element, providing transformed content and an associated feedback questionnaire to the registered user; and

gathering feedback from the registered user in response to one or more prompts included in the associated feedback questionnaire, wherein the one or more prompts request a numerical rating from the registered user, and are related to the provided transformed content and features of a specific transformation applied to the marked textual element, storing the feedback, wherein the pre-trained natural language processing model is retrained based on the stored feedback to identify and transform additional difficult comprehension areas specific to the registered user.

2. The computer-based method of claim 1 , further comprising:

storing the retrieved series of reading preference and behaviors associated with the registered user in an accessible repository.

3. The computer-based method of claim 1 , wherein automatically identifying, within the displayed content, the predicted difficult comprehension areas based on the series of preferences and behaviors associated with the registered user further comprises:

processing the displayed content using the pre-trained natural language processing model and machine learning algorithms to identify the predicted difficult comprehension areas based on the series of preferences and behaviors associated with the registered user.

4. The computer-based method of claim 1 , wherein the detected user interaction comprises the registered user clicking on the marked textual element, and wherein transforming the marked textual elements comprises at least one of word simplifications, alternative transformed content modalities, layout transformations, font transformations, style transformations, input from external learning disorder applications, input from publicly available learning disorder websites, and summarizations.

5. The computer-based method of claim 1 , further comprising:

in response to receiving the activation command, generating and outputting a notification to the registered user; and

converting a cursor to a predetermined custom cursor.

6. The computer-based method of claim 1 , wherein automatically identifying the predicted difficult comprehension areas further comprises:

processing a displayed text of the displayed content using the pre-trained natural language processing model; and

displaying using one or more visual indicators the predicted difficult comprehension areas within the displayed text of the displayed content to the registered user.

7. The computer-based method of claim 6 , wherein the one or more visual indicators includes at least highlighting one or more words within the displayed text for which simplified synonyms are available.

8. The computer-based method of claim 1 , marking the textual element associated with the predicted difficult comprehension areas, further comprises:

demarcating, within the displayed content, each textual element within the predicted difficult comprehension areas for which a corresponding transformation is available to the registered user, wherein the demarcating includes at least underlining each of the textual elements.

9. The computer-based method of claim 8 , wherein the corresponding transformation directly corresponds to the responses to the questionnaire retrieved for the registered user.

10. A computer system, the computer system comprising:

one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more computer-readable tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more computer-readable memories, wherein the computer system is capable of performing a method comprising:

retrieving responses to a questionnaire, the retrieved responses including a series of reading preferences and behaviors associated with a registered user;

receiving an activation command from the registered user;

automatically identifying, within displayed content, predicted difficult comprehension areas using a pre-trained natural language processing model based on the series of reading preferences and behaviors associated with the registered user;

marking a textual element associated with the predicted difficult comprehension areas that may be transformed to improve comprehensibility of the predicted difficult comprehension areas for the registered user;

detecting user interaction with the marked textual element;

in response to detecting user interaction with the marked textual element, transforming the marked textual element to address the predicted difficult comprehension areas based on the series of reading preferences and behaviors associated with the registered user;

in response to transforming the marked textual element, providing transformed content and an associated feedback questionnaire to the registered user; and

gathering feedback from the registered user in response to one or more prompts included in the associated feedback questionnaire, wherein the one or more prompts request a numerical rating from the registered user, and are related to the provided transformed content and features of a specific transformation applied to the marked textual element, storing the feedback, wherein the pre-trained natural language processing model is retrained based on the stored feedback to identify and transform additional difficult comprehension areas specific to the registered user.

11. The computer system of claim 10 , further comprising:

storing the retrieved series of reading preference and behaviors associated with the registered user in an accessible repository.

12. The computer system of claim 10 , wherein automatically identifying, within the displayed content, the predicted difficult comprehension areas based on the series of preferences and behaviors associated with the registered user further comprises:

processing the displayed content using the pre-trained natural language processing model and machine learning algorithms to identify the predicted difficult comprehension areas based on the series of preferences and behaviors associated with the registered user.

13. The computer system of claim 10 , wherein the detected user interaction comprises the registered user clicking on the marked textual element, and wherein transforming the marked textual elements comprises at least one of word simplifications, alternative transformed content modalities, layout transformations, font transformations, style transformations, input from external learning disorder applications, input from publicly available learning disorder websites, and summarizations.

14. The computer system of claim 10 , further comprising:

in response to receiving the activation command, generating and outputting a notification to the registered user; and

converting a cursor to a predetermined custom cursor.

15. The computer system of claim 10 , wherein automatically identifying the predicted difficult comprehension areas further comprises:

processing a displayed text of the displayed content using the pre-trained natural language processing model; and

displaying using one or more visual indicators the predicted difficult comprehension areas within the displayed text of the displayed content to the registered user.

16. A computer program product, the computer program product comprising:

one or more computer-readable tangible storage medium and program instructions stored on at least one of the one or more computer-readable tangible storage medium, the program instructions executable by a processor capable of performing a method, the method comprising:

retrieving responses to a questionnaire, the retrieved responses including a series of reading preferences and behaviors associated with a registered user;

receiving an activation command from the registered user;

automatically identifying, within displayed content, predicted difficult comprehension areas using a pre-trained natural language processing model based on the series of reading preferences and behaviors associated with the registered user;

marking a textual element associated with the predicted difficult comprehension areas that may be transformed to improve comprehensibility of the predicted difficult comprehension areas for the registered user;

detecting user interaction with the marked textual element;

in response to detecting user interaction with the marked textual element, transforming the marked textual element to address the predicted difficult comprehension areas based on the series of reading preferences and behaviors associated with the registered user;

in response to transforming the marked textual element, providing transformed content and an associated feedback questionnaire to the registered user; and

gathering feedback from the registered user in response to one or more prompts included in the associated feedback questionnaire, wherein the one or more prompts request a numerical rating from the registered user, and are related to the provided transformed content and features of a specific transformation applied to the marked textual element, storing the feedback, wherein the pre-trained natural language processing model is retrained based on the stored feedback to identify and transform additional difficult comprehension areas specific to the registered user.

17. The computer program product of claim 16 , further comprising:

storing the retrieved series of reading preference and behaviors associated with the registered user in an accessible repository.

18. The computer program product of claim 16 , wherein automatically identifying, within the displayed content, the predicted difficult comprehension areas based on the series of preferences and behaviors associated with the registered user further comprises:

processing the displayed content using the pre-trained natural language processing model and machine learning algorithms to identify the predicted difficult comprehension areas based on the series of preferences and behaviors associated with the registered user.

19. The computer program product of claim 16 , wherein the detected user interaction comprises the registered user clicking on the marked textual element, and wherein transforming the marked textual elements comprises at least one of word simplifications, alternative transformed content modalities, layout transformations, font transformations, style transformations, input from external learning disorder applications, input from publicly available learning disorder websites, and summarizations.

20. The computer program product of claim 16 , wherein automatically identifying the predicted difficult comprehension areas further comprises:

processing a displayed text of the displayed content using the pre-trained natural language processing model; and

displaying using one or more visual indicators the predicted difficult comprehension areas within the displayed text of the displayed content to the registered user.

Assignments (1)

Continuity (1)

References Cited (40)