This thesis aims to develop a system for audio fingerprinting and recognition of recorded music. Audio fingerprinting is a process used to compare audio recordings regardless of noise or other environmental factors. Throughout this work, we explore several audio fingerprinting methods and provide a detailed description of the developed system.
The system was used to index 900 songs (54 hours of recorded music) and evaluate its accuracy, indexing speed, query speed, and spatial consumption. The system is found to be sufficiently fast and accurate for use in smaller applications like archive deduplication and recognition of songs played over the radio. However, it lacks sufficient accuracy to be used to identify music played in noisy environments.
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