Inspiration
We wanted to tackle the issue of mental health using music and technology.
What it does
Users get a song recommendation based on their predicted mood based on their daily journal entry. Using Azure sentiment analysis and custom classification models, we are able to recommend a song that fits your mood.
How I built it
We used multiple API's (Genius, Spotify), a flask backend, and custom ML models to predict users moods, find similarities between song moods/lyrics and user mood.
Challenges I ran into
Connecting the front-end to the back-end (Async javascript issues) as well as connecting multiple API's together.
Accomplishments that I'm proud of
"I like our design and I think it makes Vibecheck a polished, proper product. We used a lot of different resources that we combined meaningfully." - Sina
"I am proud of what my team has accomplished and that we were able to translate the UX into the actual web app." - Jordan
"I am proud that I was able to gain a better understanding of API's and I am happy that my team was able to put together a finished, working product in time". - Michael
"I am proud that we went from concept to product in 24 hours" - Nicole
What's next for Vibecheck
tbd...
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