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Polygence Scholar2023
Anda Xie's profile

Anda Xie

Class of 2026Salt Lake City, Utah

About

I’d like to explore the following areas under the guidance of my mentor in the summer of 2024: - Non-traditional pathfinding/safety systems for autonomous vehicles. - Possibility of integrating modern pathfinding systems onto old vehicles - Usage of NLP in (financial) fraud detection My goals are 1. Complete an ISEF and publication-worthy research project 2. Publish a paper surrounding my research in a reputable journal.

Projects

  • "Silver Sync - The Application of Generative Pre-Trained Transformer Natural Language Processing (NLP-GPT) Based Intelligent Assistance Technology (IAT) on Seniors to Improve Their Safety, Increase Senior Autonomy and Decrease Social Isolation" with mentor Clark (Dec. 15, 2023)

Project Portfolio

Silver Sync - The Application of Generative Pre-Trained Transformer Natural Language Processing (NLP-GPT) Based Intelligent Assistance Technology (IAT) on Seniors to Improve Their Safety, Increase Senior Autonomy and Decrease Social Isolation

Started May 3, 2023

Abstract or project description

Seniors living alone or in a nursing home are often isolated from interpersonal interaction - be it chatting, assistance or responding to extreme situations. This leaves them in a vulnerable situation which continues to deteriorate with the increase of the aging population and stagnation of available support resources. To combat this, I aim to create a system based on cutting-edge Natural Language Processing (NLP) Generative Pre-Trained Transformer (GPT) to naturally and appropriately respond to the needs of a senior. To begin, an Automatic Speech Recognition (ASR) system parses speech from the user to determine their sentiment. Simultaneously, a Face-mesh Computer Vision (CV) system captures images of the user to identify their position, sentiment and potential needs (like the wish to interrupt). This data is sent to a cloud storage-base and automatically processed by a State Machine to identify the state of the senior and react accordingly. The state of the user as well as what they said is piped to a GPT that returns a text response and keeps a transcript for future conversational reference. This response is then output as speech via a Speech-To-Text (STT) system to the senior in a conversational way which allows them to respond.