Publication Date

Fall 2025

Degree Type

Master's Project

Degree Name

Master of Science in Computer Science (MSCS)

Department

Computer Science

First Advisor

Christopher Pollett

Second Advisor

Navrati Saxena

Third Advisor

Thomas Austin

Keywords

Yioop, Chat Enhancement, Speech-to-Text, Markdown Parsing, Summarization, Accessibility in Communication Systems

Abstract

Modern communication applications offer a variety of features to improve user experience. Interacting with other users keeps the users engaged with the application, so most modern applications offer some sort of messaging or communication features. Because of this, most users now have a mental model of the basic features that they expect from any communication system. Yioop, an open-source web platform, currently offers basic chat functionality but lacks some of these, and this project aims at bridging the gap between what is offered versus expected. This project augments Yioop’s chat system by integrating features such as audio messages, speech-to-text summary, direct translation and summary of messages and "rich text" styling using markdowns. These features improve accessibility and make the user experience better. The project was divided into two phases: The first part focused on understanding the coding structure and standards and getting familiar with the User Interface (UI) of the platform. This culminated into the main phase, which was around AI-enhanced features like text translation, transcription, and summarization. We also added helper scripts to populate test data into Yioop so that it can be used as a reference by anyone who wants to independently benchmark the work done in this project.

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Available for download on Saturday, December 19, 2026

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