GrooveFusion

Inspiration

Inspired by the vibrant energy of live DJ performances and the desire to make music mixing accessible to everyone, we aimed to create a tool that empowers users to craft unique mashups effortlessly.

What it does

GrooveFusion allows users to upload their favorite MP3 tracks, automatically analyzes energy levels, and creates high-energy mashups based on chosen hype levels, all while ensuring smooth transitions and customization options.

How we built it

We developed GrooveFusion using Python with essential libraries such as Streamlit for the web interface, Librosa for audio analysis, and Pydub for audio manipulation. The integration of a user-friendly design facilitated seamless uploads and instant feedback.

Challenges we ran into

One of the main challenges was ensuring accurate energy analysis for varied music genres, which required fine-tuning our thresholds. Additionally, managing audio quality during transitions was crucial to achieve a professional sound.

Accomplishments that we're proud of

We successfully implemented an energy-based segment selection algorithm and created a smooth user experience that allows for instant mashup creation. The positive feedback from early testers validated our efforts.

What we learned

We gained valuable insights into audio processing and the importance of user experience design. Collaborating as a team improved our problem-solving skills and helped us better understand our target audience's needs.

What's next for GrooveFusion

Next, we plan to enhance GrooveFusion by adding features like AI-driven recommendations for tracks based on user preferences, expanding support for more audio formats, and integrating a community platform for sharing mashups.

Built With

• analysis
• energy
• google-web-speech-api
• librosa
• pydub
• python
• streamlit