Organic conversations in a virtual group setting
A video conferencing system includes data relating to the focus of attention of an attendee in a virtual conference. The system determines the focus of attention of attendee as a function of the data and modifies an audio output and/or a video output of the system as a function of the focus of attention of the attendee.
1. A process comprising:
receiving into a computer device data relating to a focus of attention of a first attendee in a virtual conference;
determining the focus of attention of the first attendee as a function of the data; and
modifying one or more of an audio output and a video output of the computer device as a function of the focus of attention of the first attendee;
wherein the modifying the video output of the computer device comprises blurring the video output that is adjacent to the video output of a second attendee, and pausing the video output that is not adjacent to the video output of the second attendee.
2. The process of claim 1 , wherein eye tracking software executes the determining the focus of attention.
3. The process of claim 2 , wherein the eye tracking software determines the focus of attention of the first attendee as a function of a length of time of a gaze of the first attendee at a particular area of the computer device.
4. The process of claim 2 , wherein the determining the focus of attention of the first attendee is executed by determining that the first attendee is gazing at a second attendee displayed on the computer device and determining that the second attendee is gazing at the first attendee displayed on a second computer device associated with the second attendee.
5. The process of claim 2 , wherein the determining the focus of the first attendee is further executed via one or more of an historical analysis and a machine learning analysis.
6. The process of claim 2 , wherein the determining the focus of the first attendee is further executed using computer vision.
7. The process of claim 1 , wherein the determining the focus of the first attendee is executed via one or more of an historical analysis and a machine learning analysis.
8. The process of claim 1 , wherein the determining the focus of the first attendee is further executed using computer vision.
9. The process of claim 1 , wherein the modifying the audio output comprises raising a level of the audio output of the first attendee on a computer device of a second attendee.
10. The process of claim 1 , wherein modifying the video output comprises modifying a size of the video output of the first attendee on a computer device of a second attendee.
11. The process of claim 1 , wherein modifying the video output comprises modifying a quality of the video output of attendees other than the first attendee on a computer device of a second attendee.
12. The process of claim 1 , wherein modifying the video output comprises pausing a video output of attendees other than the first attendee on a computer device of a second attendee.
13. The process of claim 1 , wherein the modifying the one or more of the audio output and the video output of the computer device is executed in association with a panel discussion in the virtual conference.
14. The process of claim 1 , comprising:
analyzing audio data associated with the virtual conference using a natural language processing algorithm;
extracting keywords from the audio data; and
modifying the one or more of the audio output and the video output of the computer device as a function of the keywords.
15. A non-transitory machine-readable medium comprising instructions that when executed by a processor executes a process comprising:
receiving into a computer device data relating to a focus of attention of a first attendee in a virtual conference;
determining the focus of attention of the first attendee as a function of the data; and
modifying one or more of an audio output and a video output of the computer device as a function of the focus of attention of the first attendee;
wherein the modifying the video output of the computer device comprises blurting the video output that is adjacent to the video output of a second attendee, and pausing the video output that is not adjacent to the video output of the second attendee.
16. The non-transitory machine-readable medium of claim 15 , wherein eye tracking software executes the determining the focus of attention.
17. The non-transitory machine-readable medium of claim 16 ,
wherein the determining the focus of attention of the first attendee is executed by determining that the first attendee is gazing at a second attendee displayed on the computer device and determining that the second attendee is gazing at the first attendee displayed on a second computer device associated with the second attendee; and
wherein the determining the focus of the first attendee is further executed via one or more of an historical analysis and a machine learning analysis.
18. The non-transitory machine-readable medium of claim 15 , comprising instructions for:
analyzing audio data associated with the virtual conference using a natural language processing algorithm;
extracting keywords from the audio data; and
modifying the one or more of the audio output and the video output of the computer device as a function of the keywords.
19. A system comprising:
a computer processor; and a computer memory coupled to the computer processor: wherein one or more of the computer processor and the computer memory are operable for:
receiving into a computer device data relating to a focus of attention of a first attendee in a virtual conference; determining the focus of attention of the first attendee as a function of the data; and modifying one or more of an audio output and a video output of the computer device as a function of the focus of attention of the first attendee; wherein the modifying the video output of the computer device comprises blurring the video output that is adjacent to the video output of a second attendee, and pausing the video output that is not adjacent to the video output of the second attendee.