This project focuses on the development of conversational analytics and AI solutions for Seasalt.ai, aimed at analyzing real-world speech data for insights. Multiple Machine Learning models were implemented, with Convolutional Neural Networks (CNN) demonstrating the highest accuracy improvement of approximately 67%. The CNN model effectively identifies emotions from audio data clips, enhancing conversational analytics within Seasalt.ai's product SeaMeet. Extensive experiments and evaluations have been conducted to validate the effectiveness of the CNN-based approach, showcasing its potential for real-time applications such as affective computing, virtual assistants, and emotion-aware human-computer interaction.

Experiences of dissatisfaction are a pervasive issue in today's society, however, there are few information solutions available that specifically address this within pregnant or postpartum individuals. Recognizing that negative body perception can cause significant distress to both the parent and their child, Team U has developed a solution that fundamentally prioritizes mental health and well-being: reflect. reflect is a full-body smart mirror that integrates daily check-ins, intention setting, breathing exercises, reflection time, and mirror exposure therapy. Our goal is to encourage users to slow down, cultivate healthier relationships with themselves, and ultimately, help improve their quality of life.