Audio enhancement and intelligent classification of household sound events using a sparsely deployed array
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 11-24 |
Journal / Publication | Journal of the Acoustical Society of America |
Volume | 147 |
Issue number | 1 |
Online published | 13 Jan 2020 |
Publication status | Published - Jan 2020 |
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Abstract
A household sound event classification system consisting of an audio localization and enhancement front-end cascaded with an intelligent classification back-end is presented. The front-end is composed of a sparsely deployed microphone array and a preprocessing unit to localize the source and extract the associated signal. In the front-end, a two-stage method and a direct method are compared for localization. The two-stage method introduces a subspace algorithm to estimate the time difference of arrival, followed by a constrained least squares algorithm to determine the source location. The direct localization methods, the delay-and-sum beamformer, the minimum power distortionless response beamformer, and the multiple signal classification algorithm are compared in terms of localization performance for sparse array configuration. A modified particle swarm optimization algorithm enabled an efficient grid-search. A minimum variance distortionless response beamformer in conjunction with a minimum-mean-square-error postfilter is exploited to extract the source signals for sound event classification tasks that follow. The back-end of the system is a sound event classifier that is based on convolutional neural networks (CNNs), and convolutional long short-term memory networks Mel-spectrograms are used as the input features to the CNNs. Simulations and experiments conducted in a live room have demonstrated the strength and weakness of the direct and two-stage methods. Signal quality enhancement using the array-based front-end proves beneficial for improved classification accuracy over a single microphone. © 2020 Acoustical Society of America.
Citation Format(s)
Audio enhancement and intelligent classification of household sound events using a sparsely deployed array. / Bai, Mingsian R.; Lan, Shih-Syuan; Huang, Jong-Yi; Hsu, Yi-Cheng; So, Hing-Cheung.
In: Journal of the Acoustical Society of America, Vol. 147, No. 1, 01.2020, p. 11-24.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review