DEVICE IMPLEMENTED LEARNING VALIDATION

• US 20150046161A1
• Filed: 08/07/2013
• Published: 02/12/2015
• Est. Priority Date: 08/07/2013
• Status: Active Application

• Current Assignee: Lenovo Singapore Pte Limited (Lenovo Group Ltd.)
• Original Assignee: Lenovo Singapore Pte Limited (Lenovo Group Ltd.)
• Inventors: Locker, Howard, Cheston, Richard Wayne, Wibran, Goran Hans, Nicholson, John Weldon
• Application Number:
  US13/961,542
• Publication Number:
  US 20150046161A1
• Time in Patent Office: Days
• US Class Current: 704/246
• CPC Class Codes: G09B 5/00 Electrically-operated educational appliances working with questions and answers G09B7/00; simulators G09B9/00; advertising or displaying in general G09F
• CPC Class Codes: G09B 5/06 with both visual and audible presentation of the material to be studied
• CPC Class Codes: G09B 7/02 of the type wherein the student is expected to construct an answer to the question which is presented or wherein the machine gives an answer to the question presented by a student
• CPC Class Codes: G10L 15/00 Speech recognition G10L17/00 takes precedence

Abstract

An aspect provides a method, including: collecting, at one or more device sensors, one or more inputs selected from the group of inputs consisting of audio inputs from a learning environment and visual inputs from a learning environment; processing, using one or more processors, the one or more inputs to detect an unauthorized behavior pattern; mapping, using the one or more processors, the unauthorized behavior pattern to a predetermined action; and executing the predetermined action. Other aspects are described and claimed.

Claims

1. A method, comprising:

collecting, at one or more device sensors, one or more inputs selected from the group of inputs consisting of audio inputs from a learning environment and visual inputs from a learning environment;

processing, using one or more processors, the one or more inputs to detect an unauthorized behavior pattern;

mapping, using the one or more processors, the unauthorized behavior pattern to a predetermined action; and

executing the predetermined action.

2. The method of claim 1, wherein the processing comprises analyzing the audio inputs to detect more than one speaker;

the analyzing the audio inputs to detect more than one speaker comprising detecting, using data derived from a microphone array, distinguishable speech data signals within the audio inputs collected.

3. The method of claim 2, wherein the analyzing the audio inputs to detect more than one speaker comprises performing speaker recognition analysis to recognize at least one of two or more speakers detectable in the audio inputs collected.

4. The method of claim 2, wherein the analyzing the audio inputs to detect more than one speaker comprises performing speaker detection analysis to distinguish two or more speakers in the audio inputs collected.

5. The method of claim 1, wherein the detecting an unauthorized behavior pattern comprises accessing a data store of audio analysis information and comparing processed audio inputs collected from the learning environment to the audio analysis information.

6. The method of claim 5, wherein the data store of audio analysis information comprises audio analysis information selected from the group of audio analysis information consisting of:

audio analysis information derived from a group of users; and

audio analysis information derived from a single user.

7. The method of claim 1, wherein the detecting an unauthorized behavior pattern comprises accessing a data store of visual analysis information and comparing processed visual inputs collected from the learning environment to the visual analysis information.

8. The method of claim 1, wherein the processing comprises analyzing the visual inputs to detect a gaze pattern of a user;

and

wherein the detecting an unauthorized behavior pattern comprises accessing a data store of visual analysis information and comparing the gaze pattern of the user to stored visual analysis information.

9. The method of claim 1, wherein the detecting an unauthorized behavior pattern comprises accessing additional data responsive to an initial detection of an unauthorized behavior pattern.

10. The method of claim 9, wherein the additional data comprises data derived from one or more test inputs provided by a user selected from the group of users consisting of:

a user providing the visual information collected and another user located in the same learning environment.

12. The apparatus of claim 1, wherein to process comprises analyzing the audio inputs to detect more than one speaker;

the analyzing the audio inputs to detect more than one speaker comprising detecting, using data derived from a microphone array, distinguishable speech data signals within the audio inputs collected.

13. The apparatus of claim 12, wherein the analyzing the audio inputs to detect more than one speaker comprises performing speaker recognition analysis to recognize at least one of two or more speakers detectable in the audio inputs collected.

14. The apparatus of claim 12, wherein the analyzing the audio inputs to detect more than one speaker comprises performing speaker detection analysis to distinguish two or more speakers in the audio inputs collected.

11. An information handling device, comprising:

one or more of an audio sensor and a visual sensor;

one or more processors; and

a memory accessible to the one or more processors storing instructions executable by the one or more processors to;

collect, at one or more of the audio sensor and the visual sensor, one or more inputs selected from the group of inputs consisting of audio inputs from a learning environment and visual inputs from a learning environment;

process the one or more inputs to detect an unauthorized behavior pattern;

map the unauthorized behavior pattern to a predetermined action; and

execute the predetermined action.

15. The apparatus of claim 11, wherein to detect an unauthorized behavior pattern comprises accessing a data store of audio analysis information and comparing processed audio inputs collected from the learning environment to the audio analysis information.

16. The apparatus of claim 15, wherein the data store of audio analysis information comprises audio analysis information selected from the group of audio analysis information consisting of:

audio analysis information derived from a group of users; and

audio analysis information derived from a single user.

17. The apparatus of claim 11, wherein to detect an unauthorized behavior pattern comprises accessing a data store of visual analysis information and comparing processed visual inputs collected from the learning environment to the visual analysis information.

18. The apparatus of claim 11, wherein to process comprises analyzing the visual inputs to detect a gaze pattern of a user;

and

wherein to detect an unauthorized behavior pattern comprises accessing a data store of visual analysis information and comparing the gaze pattern of the user to stored visual analysis information.

19. The apparatus of claim 11, wherein to detect an unauthorized behavior pattern comprises accessing additional data responsive to an initial detection of an unauthorized behavior pattern;

wherein the additional data comprises data derived from one or more test inputs provided by a user selected from the group of users consisting of;

a user providing the visual information collected and another user located in the same learning environment.

20. A product, comprising:

a computer readable storage medium storing instructions executable by one or more processors, the instructions comprising;

computer readable program code configured to collect, at one or more device sensors, one or more inputs selected from the group of inputs consisting of audio inputs from a learning environment and visual inputs from a learning environment;

computer readable program code configured to process the one or more inputs to detect an unauthorized behavior pattern;

computer readable program code configured to map the unauthorized behavior pattern to a predetermined action; and

computer readable program code configured to execute the predetermined action.