Study of statistical robust closed set speaker identification with feature and score-based fusion

Al-Kaltakchi, Musab, Woo, Wai Lok, Dlay, Satnam and Chambers, Jonathon (2016) Study of statistical robust closed set speaker identification with feature and score-based fusion. In: 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE. ISBN 978-1-4673-7804-8

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Abstract

In this paper, the statistical combination of Power Normalization Cepstral Coefficient (PNCC) and Mel Frequency Cepstral Coefficient (MFCC) features in robust closed set speaker identification is studied. Feature normalization and warping together with late score-based fusion are also exploited to improve performance in the presence of channel and noise effects. In addition, combinations of score and feature-based approaches are considered with early and/or late fusion; these systems use different feature dimensions (16, 32). A 4th order G.712 type IIR filter is employed to represent handset degradation in the channel. Simulation studies based on the TIMIT database confirm the improvement in Speaker Identification Accuracy (SIA) through the combination of PNCC and MFCC features in the presence of handset and Additive White Gaussian Noise (AWGN) effects.

Item Type:	Book Section
Uncontrolled Keywords:	Robust closed set speaker identification, early and late fusion, handset, AWGN, G.712 handset
Subjects:	G400 Computer Science
Department:	Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User:	Becky Skoyles
Date Deposited:	09 Apr 2019 12:24
Last Modified:	10 Oct 2019 20:16
URI:	http://nrl.northumbria.ac.uk/id/eprint/38864

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