Privacy-centric virtual assistant for unified communication infrastructure with physics-enhanced denoising and modular protocol

A virtual assistant system comprising:

• an electronic device comprising:
• a meeting application configured to facilitate virtual communication between two or more people;
• and
• a processor configured to:
• capture unstructured data from the meeting application;
• denoise, using a physics informed neural network, audio data from the unstructured data, the physics informed neural network being of a size for deployment on low-computational devices;
• generate, using one or more computerized models, one or more training datasets from the unstructured data and the denoised audio data, the one or more training datasets being tailored for meeting application-specific contexts;
• generate a virtual assistant model, the virtual assistant model being of a size for deployment on low-computational devices;
• train, using the one or more training datasets, the virtual assistant model to respond to queries regarding the meeting application infrastructure or device management;
• and
• deploy the virtual assistant model on the meeting application for use by an end user, wherein the virtual assistant model provides control over UC infrastructure using natural language voice/text commands, including configuring devices, provisioning network settings, diagnose problems, and automating administrative tasks.

A method for denoising audio data using a physics informed neural network, the method comprising:

• receiving unstructured data comprising audio or video data;
• training the physics informed neural network with acoustic wave equations to distinguish speech from noise and to remove the noise, the physics informed neural network being of a size for deployment on low-computational devices;
• and
• denoising the audio or video data using the trained physics informed neural network to generate denoised audio or video data.