RingCentral, Inc. (20240212248). SYSTEM AND METHOD FOR GENERATING AVATAR OF AN ACTIVE SPEAKER IN A MEETING simplified abstract
Contents
SYSTEM AND METHOD FOR GENERATING AVATAR OF AN ACTIVE SPEAKER IN A MEETING
Organization Name
Inventor(s)
Igor Vladimirovich Kamyshev of Tbilisi (RU)
SYSTEM AND METHOD FOR GENERATING AVATAR OF AN ACTIVE SPEAKER IN A MEETING - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240212248 titled 'SYSTEM AND METHOD FOR GENERATING AVATAR OF AN ACTIVE SPEAKER IN A MEETING
The method described in the abstract involves creating an avatar that mimics appropriate facial movements associated with audio data.
- Receiving facial data of a participant user
- Generating an avatar data based on the facial data using a machine learning model
- Receiving data related to facial movement
- Training the generated avatar based on the facial movement data using a second machine learning model
- Generating a trained avatar data that mimics appropriate facial movements associated with audio data
Potential Applications: - Virtual reality applications - Video conferencing platforms - Gaming industry for realistic avatars - Educational tools for language learning and speech therapy
Problems Solved: - Enhancing user experience in virtual environments - Improving communication through avatars - Providing a more engaging and interactive experience in digital platforms
Benefits: - Realistic facial expressions in avatars - Enhanced communication in virtual settings - Personalized user experience - Improved engagement and immersion in virtual environments
Commercial Applications: Title: "Enhanced Avatar Technology for Virtual Environments" This technology can be utilized in various industries such as virtual reality, gaming, education, and communication platforms to enhance user experience and engagement. The market implications include increased demand for advanced avatar technologies in digital applications.
Questions about Avatar Technology: 1. How does this technology impact user engagement in virtual environments? 2. What are the potential limitations of using machine learning models for training avatars?
Frequently Updated Research: Stay updated on advancements in machine learning algorithms for avatar creation and facial recognition technologies to enhance the performance and realism of trained avatars.
Original Abstract Submitted
a method includes receiving a facial data associated with a participant user; generating an avatar data of the participant user based on the facial data using a first machine learning (ml) model; receiving data associated with facial movement; and training the generated avatar based on the data associated with facial movement using a second ml model to generate a trained avatar data, wherein the trained avatar data mimics appropriate facial movements associated with audio data.
