Title: Enhanced perceptual feature space with context drift information for query by humming system

Authors: Trisiladevi C. Nagavi; Nagappa U. Bhajantri

Addresses: Department of Computer Science and Engineering, S.J. College of Engineering, Mysore, Karnataka, India ' Department of Computer Science and Engineering, Government Engineering College, Chamarajanagar, Karnataka, India

Abstract: The innovations in the realm of music signal processing insist on adept music information retrieval (MIR) techniques. In this paper, we propose a query by humming (QBH) MIR system for retrieving the desired song based on enhanced perceptual feature set, context drift information (CDI) and humming query (HQ). In the proposed system, eight perceptual features corresponding to four perceptual properties are extracted. Subsequently, the CDI of these features is analysed and estimated through the perceptual transfer entropy (PTE) measure. Then, the perceptual feature space and PTE trajectory of the target music database is matched with the HQ. The effectiveness of the proposed approach is substantiated with series of experiments, consisting of 1,200 songs target database and 200 HQs. The target database of 1,200 songs is converted into 1,495 fragments by splitting each song into several small proportions. The results show that the proposed method effectively finds the target song with HQ as input.

Keywords: context drift information; CDI; perceptual features; query by humming; QBH; perceptual transfer entropy; PTE; music signal processing; music information retrieval; feature extraction; song retrieval.

DOI: 10.1504/IJRIS.2015.072942

International Journal of Reasoning-based Intelligent Systems, 2015 Vol.7 No.3/4, pp.161 - 170

Received: 20 Sep 2014
Accepted: 05 Nov 2014

Published online: 09 Nov 2015 *

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