Simulating Shazam: Acoustic Fingerprinting for Music Identification A Comprehensive Study on Developing a Song Recognition System

Sammanfattning

AbstractThis report explains the implementation, design and testing of the core functionalities of Shazam. Shazam identifies songs by capturing short audio segments and matches them against a sizeable database. The program is coded in Python and with MySQL for the database. To perform tests, both audio files and a microphone are used to catch the samples of the songs. The results of the project are deemed successful as it can detect songs from a 10 second sample of a song. In conclusion, the project demonstrates a strong foundation to continue developing the project to simulate Shazam.