Humming feature extraction based on locality statistical analysis

Abstract

This paper presents a novel humming feature extraction algorithm based on locality statistical analysis to tackle the problem of the instability of humming features in the query by humming (QBH) system. By carrying out statistics to humming notes sequences in both longitudinal vocal range distribution and horizontal temporal variation distribution, we can obtain the locality statistical humming features. And we concatenate several features using the idea of N-gram to improve feature discrimination. In the framework of QBH based on Locality Sensitive Hashing (LSH), the proposed method has achieves 86% top-1 rate and 92% top-5 rate in the experiment, indicating the effectiveness of the method.