Simulating Shazam: Acoustic Fingerprinting for Music Identification A Comprehensive Study on Developing a Song Recognition System
Typ
Examensarbete på kandidatnivå
Bachelor Thesis
Bachelor Thesis
Program
Elektroteknik 180 hp (högskoleingenjör)
Publicerad
2024
Författare
Gyllenhammar, Rasmus
Lennernäs, Christoffer
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
Abstract
This 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.