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Polyphonic Sound Event Tracking using Linear Dynamical Systems

Benetos, E, Lafay, G, Lagrange, M and Plumbley, Mark (2017) Polyphonic Sound Event Tracking using Linear Dynamical Systems IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 25 (6). pp. 1266-1277.

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Abstract

In this paper, a system for polyphonic sound event detection and tracking is proposed, based on spectrogram factorisation techniques and state space models. The system extends probabilistic latent component analysis (PLCA) and is modelled around a 4-dimensional spectral template dictionary of frequency, sound event class, exemplar index, and sound state. In order to jointly track multiple overlapping sound events over time, the integration of linear dynamical systems (LDS) within the PLCA inference is proposed. The system assumes that the PLCA sound event activation is the (noisy) observation in an LDS, with the latent states corresponding to the true event activations. LDS training is achieved using fully observed data, making use of ground truth-informed event activations produced by the PLCA-based model. Several LDS variants are evaluated, using polyphonic datasets of office sounds generated from an acoustic scene simulator, as well as real and synthesized monophonic datasets for comparative purposes. Results show that the integration of LDS tracking within PLCA leads to an improvement of +8.5-10.5% in terms of frame-based F-measure as compared to the use of the PLCA model alone. In addition, the proposed system outperforms several state-of-the-art methods for the task of polyphonic sound event detection.

Item Type: Article
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Benetos, EUNSPECIFIEDUNSPECIFIED
Lafay, GUNSPECIFIEDUNSPECIFIED
Lagrange, MUNSPECIFIEDUNSPECIFIED
Plumbley, Markm.plumbley@surrey.ac.ukUNSPECIFIED
Date : 1 June 2017
Identification Number : 10.1109/TASLP.2017.2690576
Copyright Disclaimer : (c) 2017. IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
Uncontrolled Keywords : Sound event detection, linear dynamical systems, probabilistic latent component analysis, sound scene analysis.
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 14 Feb 2017 17:36
Last Modified : 19 Jul 2017 10:20
URI: http://epubs.surrey.ac.uk/id/eprint/813536

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