Development of a Hummed-Based Query System for Music Retrieval

Abstract

This research aims to improve query by humming (QBH) systems, enabling users to find music by humming a tune into a device. The project uses optimized database indexing, advanced machine learning techniques, and signal processing to process diverse humming inputs. The prototype, developed using a Laravel-based web application and Python, is expected to improve music discovery and user interaction, laying the groundwork for future MIR systems.