FORREST | Team Website

About the Project

Transforming unstructured video opinions into navigable, verifiable argument graphs.

FORREST is a research-focused argument analysis system for political opinions and current affairs. Users post short face-camera opinion videos on trending topics. Other users reply with their own videos, creating a branching debate tree. Our AI pipeline transcribes each video, classifies its stance as FOR, AGAINST, or UNRESOLVED, and links every classification to an exact transcript excerpt and timestamp — making the entire discussion structure traceable and auditable.

Project Roadmap

Our phased approach to building FORREST.

Phase 1 — Define & Annotate

Focus on political-opinion videos, collect 20 videos, and create human-annotated ground truth using FOR / AGAINST / UNRESOLVED labels.

Phase 2 — AI Argument Recovery

Transcribe videos using OpenAI Whisper and identify stances with exact timestamps and evidence using Gemini/GPT-4o API.

Phase 3 — Build Debate Graph

Convert relationships into a Root → Reply → Reply argument tree and visualize the discussion as an interactive graph.

Phase 4 — Evaluate the System

Compare FORREST with transcript/summary-based baselines using Precision, Recall, F1, stance accuracy, and Fleiss' Kappa.

Phase 5 — Full Platform

Add community verification, credibility scoring, moderation, recommendations, and private collaborative trees.

Our Team

Group 1 • UCS503 Software Engineering Lab

Sahibnoor Singh

Team Lead & Backend Architect

Role: Leads the project SDLC, coordinates tasks, designs the REST API, and handles database management & deployment.
Qualifications: Independent game publisher with Voodoo, strong backend engineering skills, and system architecture experience.

Yaksh

Ideation & Domain Specialist

Role: Conceptualized the core FORREST app idea and defined the domain of political opinions and argument trees.
Qualifications: Strong domain knowledge in current affairs and conceptual product design.

Ridhima

Frontend Developer & UI/UX

Role: Develops the client-facing static website using HTML/CSS/JS and ensures a premium, responsive design.
Qualifications: Skilled in modern web design frameworks, typography, and frontend interactivity.

Jasmine Tiwana

AI Researcher & Data Annotator

Role: Handles the FORREST core logic—transcribing videos, prompting Gemini API, and calculating baseline F1 scores.
Qualifications: Background in Natural Language Processing (NLP) and argument mining.

Current Status

Active Planning Phase — Preparing Planning Presentation v1