Team Roster

Team Members

• Raef Maroof - Created python script for drawing pitch vectors from spotify, as well as script for normalizing pitch vectors to fixed time intervals. Created code for training and evaluating linear, rbf, and polynomial models. Helped train all models except quadratic. Created code for postAudio endpoint. Wrote frontend code linking to postAudio endpoint. Wrote frontend code linking to ShazamKit. Helped write frontend code connecting frontend and backend through the getsongs endpoint.
• Arsh Patel - Created a python script to get the pitch vectors of each song in the database. Created a python script to normalize the pitch vectors of both the training data and audio file sent from the frontend. Helped train the quadratic-classification machine learning model to identify songs. Helped create the getSong endpoint.
• Cooper Hickmott
• Grant Marshall - Created a web scraper to gather movie data from IMDb's website. The data includes notable movie and soundtrack information from IMDb's top 100 rated movies. Set up AWS server with Python/Django web framework and Postgres database to hold movie and soundtrack information. Created endpoints to be used by the front end which returns a list of movies that contains a given song and other relevant information.
• Henry Beckstein
• Siddharth Nagamangala - Helped get pitch vectors from Spotify in python script and helped normalize the pitch vectors. Worked on developing SVM machine learning models such as linear and multiclass and also wrote methods in order to measure model training performance and save the models. Helped train multiclass model to see if it was a viable model for song identification.
• Xinyi Chen