Self-learning wearable artificial-intelligence system for real-time in-person conversation coaching

A system for coaching a user during a live, in-person conversation, the system comprising:

• a head-worn wearable device configured to be worn by the user, the wearable device comprising a microphone, a camera oriented to capture an environment of the user, and an audio output;
• and
• one or more processors and memory storing instructions that, when executed by the one or more processors, cause the system to:
• capture, via the microphone and the camera, audio of the conversation and video of one or more other persons who are physically present with the user;
• generate, using a generative artificial-intelligence model, a suggestion of what the user should say to the one or more physically present persons during the live, in-person conversation, based at least in part on the audio, and present the suggestion to the user in real time through the audio output;
• capture, after the suggestion is presented, an in-person reaction of the one or more physically present persons, including a non-verbal reaction detected from the video, occurring after the user speaks in accordance with the suggestion;
• determine, from the in-person reaction, an outcome signal indicating whether the in-person reaction was favorable;
• and
• update the generative artificial-intelligence model using the outcome signal, such that the model is personalized to the user and biased toward generating suggestions that elicit favorable in-person reactions from physically present persons.

A computer-implemented method for coaching a user during a live, in-person conversation, the method comprising:

• generating, using a generative artificial-intelligence model, a suggestion of what the user should say to one or more other persons who are physically present with the user during a live, in-person conversation, and presenting the suggestion to the user in real time through a wearable device worn by the user;
• capturing, by one or more sensors of the wearable device after the suggestion is presented, an in-person reaction of the one or more physically present persons occurring after the user speaks in accordance with the suggestion;
• determining, from the captured in-person reaction, an outcome signal indicating whether the in-person reaction was favorable;
• and
• updating the generative artificial-intelligence model using the outcome signal, such that the model is personalized to the user and biased toward generating suggestions that, for the user, elicit favorable in-person reactions from physically present persons in subsequent live, in-person conversations.

A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to:

• generate, using a generative artificial-intelligence model, a suggestion of what a user should say to one or more other persons who are physically present with the user during a live, in-person conversation, and present the suggestion to the user in real time through a wearable device worn by the user;
• capture, by one or more sensors of the wearable device after the suggestion is presented, an in-person reaction of the one or more physically present persons occurring after the user speaks in accordance with the suggestion;
• determine, from the captured in-person reaction, an outcome signal indicating whether the in-person reaction was favorable;
• and
• update the generative artificial-intelligence model using the outcome signal, such that the model is biased toward generating suggestions that elicit favorable in-person reactions from physically present persons.