This repository contains the final report for GrapeVine, a conceptual product design project completed for CSS 350 (Software Engineering) at the University of Washington Bothell.
GrapeVine is a proposed cross-platform language translation application that integrates Natural Language Processing (NLP), Machine Learning (ML), and sentiment analysis to capture cultural and regional nuances in real-time speech and text.
The goal was to design a system capable of context-aware translations that go beyond word-for-word substitution, supporting dialects, slang, and emotional tone.
- Final Report (PDF): Includes requirements analysis, high-level architecture, proposed features, market analysis, development lifecycle, and success metrics.
- Team Contributions: Work was completed collaboratively as part of a 5-person team project.
- Requirements gathering and technical writing
- System and software architecture design
- Product planning and lifecycle documentation
- Application of NLP, ML, and sentiment analysis concepts
This was a conceptual class project — no production code was developed. The focus is on design, planning, and documentation, showcasing technical communication and product design skills.