Warping indexes with envelope transforms for query by humming

Abstract

A Query by Humming system allows the user to find a song by humming part of the tune. No musical training is needed. Previous query by humming systems have not provided satisfactory results for various reasons. Some systems have low retrieval precision because they rely on melodic contour information from the hum tune, which in turn relies on the error-prone note segmentation process. Some systems yield better precision when matching the melody directly from audio, but they are slow because of their extensive use of Dynamic Time Warping (DTW). Our approach improves both the retrieval precision and speed compared to previous approaches. We treat music as a time series and exploit and improve well-developed techniques from time series databases to index the music for fast similarity queries. We improve on existing DTW indexes technique by introducing the concept of envelope transforms, which gives a general guideline for extending existing dimensionality reduction methods to DTW indexes. The net result is high scalability. We confirm our claims through extensive experiments.