Emoticue

Inspiration:

We’ve all been there, scrolling endlessly to find a movie that resonates with us or music that matches our mood. That’s where EmotiCue came from. We wanted to eliminate the guesswork in discovering content. It listens, understands, and recommends based on what truly matters: your mood.

What EmotiCue Does:

EmotiCue is a straightforward mood journal inspired by AI. It does more than just record your thoughts; it sees the deeper meaning. When you share how you’re feeling, EmotiCue analyzes the emotions in your entry and quickly suggests movies, songs, and books that align with your vibe.Everything operates locally using a curated recommendation system; there’s no need for external APIs. Whether you're feeling great, stuck in a rut, or somewhere in between, EmotiCue helps you find the perfect soundtrack, story, or film for the moment.

How We Built It

Frontend: The interface is built with HTML, styled using Tailwind(minimal) CSS for a clean, responsive look, and powered by vanilla JavaScript for all interactions. Mood Detection: We examine journal entries to detect emotional tone and keywords. This lets EmotiCue classify your mood accurately. Local Recommendation Engine: Instead of relying on APIs, the app retrieves all its content from a well-structured hardcoded, making it lightweight, fast, and entirely self-sufficient. Structure: Mood is analyzed, matched, and then used to fetch content suggestions in real-time, offering a seamless experience for users.

Challenges We Faced:

Emotional Nuance: Interpreting emotional text meaningfully using only JavaScript took a lot of trial and error. Lightweight Design: We chose not to use heavy frameworks. Crafting a smooth, modern interface with just the basics was a creative challenge.

Accomplishments We’re Proud Of:

Mood-based matching that feels personal and relevant.
A fast, no-dependency UI that works well on any device.
Built a self-contained app that functions without external APIs; it simply works.

What We Learned:

How to analyze natural language for mood detection with a minimal tech stack.
Ways to enhance UX/UI without relying on frameworks like React or Vue.

What’s Next for EmotiCue:

Spotify or music API integration for live recommendations.
Intgrating machine learning to improve accuracy over time based on user feedback.
A mood history tracker to reflect on emotional trends.
A fully responsive or native mobile app for on-the-go journaling and content discovery.

Built With

Submitted to

CS Girlies Hackathon - A.I vs H.I

Created by

I worked on the documentation and demo video part. Also helped other members troubleshoot problems in the code. Soon, we will link API’s as well for smoother functioning( working on it).

Arrsshh-dev Kaur
I helped with the frontend, organizing files and making the mascot sprites.

Izzy-droid .
Came up with the idea, Developed the front-end, helped in debugging and the design of the website.

Huriya Irfan
helped with backend api linking,documentation and overall project management and demo

Nishant Acharya
I contributed to the project by coming up with the website name and supporting the frontend development. I helped debug layout issues, enhance the user interface, and resolve Git-related problems to ensure smooth collaboration. Additionally, I worked on setting up the login and signup functionality using Firebase Authentication. While we couldn’t fully integrate it due to time constraints, the setup and logic are in place for future implementation.

yasvi tank
Damon