MuSentence

This is a sample of when the project is run without any input from the user.
This is a sample when a phrase is inputted into the search bar. This will return a random personalized song.
This is a sample when a phrase that is inputted is invalid. We wanted to make a joke instead of ruining the process for the user.

Inspiration:

Sometimes when listening to music we want to be able to search for something new.

Sometimes we want a song for our emotions or we think of something.

Our Project aims to be this branch for people in order to allow them to enjoy new music from a quick search!

What does our project do?

MuSentence takes a user's sentence and finds the best song for that phrase based on their mood.

After searching a user can simply click the album cover and get a link to all its information.

From there a user can click on a button to take them to the streaming service of their choice and listen to their songs.

How we built:

We used VSCode with a combination of GitHub and LiveShare in order to work together.

VSCode was used to work on the project and combine Python along with JavaScript calculations.

LiveShare and GitHub were used for remote and shared coding to work on the project effectively.

Finally, Django was used to bridge our Python calculations with our React.JS website.

Challenges:

Getting started with React was difficult initially since we had never used React and created a website from scratch. It took us a while to get comfortable with the design and the new tools associated with it. More specifically, we struggled with the dynamic nature of React and how it renders and rerenders components. The useState was also something that we struggled with getting used to.

Along with this, we had a lot of design decisions to consider. From color palettes to fonts to formats we were constantly discussing and changing design ideas while creating our React websites.

But our biggest challenge was Django since it was new to all of us and had a steep learning curve. The ideas took us a while to implement but once completed we were able to complete everything with relative ease.

Accomplishments:

We are proud of the implementation of the projects since we accomplished all the goals we had planned when starting the projects.

Along with this, we were able to circumvent a lot of problems we ran into. Through teamwork and research, a lot of our ideas were able to be created.

Finally, we were most proud of how much we learned during the project. From connecting Python and JavaScript to creating a React website we learned a lot through this process. Since this was most of our first hackathons we believe we made the most out of it.

What's next for MuSentence:

We would like to create some more features like a setting tab for more personalized data. This would make songs more personalized to fit someone's specific taste like certain types of genres.

There was also another category of data that all of the songs had called the seeded mood word. For example, for Eminem's Till I Collapse, the seeded mood word is 'aggressive'. In the future, we would like to use the Natural Language Toolkit to try to determine the representative mood word of a sentence and compare that to those in the dataset.

Along with this, we had ideas of finding where people came from in order to locate who is using the app the most in the world. This would also allow us to use more features React has to offer.