System and method to improve video conferencing using presence metrics
A system and method of image analytics, computer vision focused on monitoring specific virtual presence metrics will provide each individual user with consistent progress reports and live feedback during video meetings. Machine learning and AI are leveraged to provide professionals with feedback and coaching according to virtual presence metrics in order to develop a new skill set through and elevate the user's virtual presence. Pre-trained machine learning models combined with the founders own thought leadership in nonverbal communication, presence and body language assists in assessing posture, gesture, eye contact, filler words and speech metrics, sentiment analysis and other presence and communication features.
1. A computer-implemented method to improve video conferencing assessment of a user using a virtual presence system, the virtual presence system comprising a processor, a browser-based virtual presence assessment application and a video conferencing application, the method comprising the steps of:
launching or starting the browser-based virtual presence assessment application and the video conferencing application;
authenticating the user with the browser-based virtual presence assessment application video conferencing application;
downloading one or more pre-trained machine learning models locally on the user computer, the pre-trained machine learning models configured to work with the virtual presence assessment application;
initiating a video conferencing assessment on the user computer;
evaluating the recorded video conference session for presence metrics;
displaying visual feedback nudges to the user to allow them to course correct in real-time or near real-time; and
providing a report with presence metric scores and feedback based on analysis to the user;
wherein evaluating the video conference session further comprises evaluating non-verbal presence metrics as indicators of confidence;
wherein evaluating the video conference session further comprises using artificial intelligence (AI) or machine learning (ML) algorithms to automatically conduct the assessment in real-time or near real-time;
wherein the feedback is made using pre-trained machine learning models, computer vision and image analytics;
wherein the presence metrics include metrics to evaluate posture and framing as influencing factors to provide the feedback;
wherein the machine learning algorithm is used to identify the landmarks of the user's face, upper body, and hands;
wherein the pre-trained machine learning models are configured to analyze the video conferencing session in real-time to analyze human behaviors;
wherein the video conferencing assessment is stored locally on the user computer and is not sent over the internet to a server.
2. The computer-implemented method of claim 1 wherein the non-verbal presence metrics further include metrics to evaluate gesture, eye contact, filler words and speech metrics, sentiment analysis and other customizable features.
3. The computer-implemented method of claim 1 wherein the feedback includes constructive feedback for improvement.
4. The computer-implemented method of claim 1 wherein artificial intelligence is used to take these landmarks to classify the user's energy, empathy, confidence, rapport building and expression during video calls and events.
5. The computer-implemented method of claim 1 where the machine learning algorithm is used to analyze audio and identify sounds, frequencies, emotions, utterances and words spoken.