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Title: Using regularized fisher discriminant analysis to improve the performance of Gaussian supervector in session and device identification
Authors: Leung, FHF 
Jiang, Y 
Keywords: Audio forensics
Projected Gaussian Supervector
Recording device identification
Regularized Fisher Discriminant Analysis
Telephone session identification
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers
Source: Proceedings of the International Joint Conference on Neural Networks, 2017, 7965921, p. 705-712 How to cite?
Abstract: In this paper, we propose Regularized Fisher Discriminant Analysis (RFDA) as a projection method applied on Gaussian Supervector (GSV). GSV was originally applied on speaker recognition and verification, and has exhibited good performance. Recently GSV has also been applied in audio forensics area, such as recording device identification. It has been shown that GSV can also capture useful information related to the recording device. In this paper, we show that GSV can also be applied in telephone session identification. However, although GSV can capture useful information for different identification purposes, the performance of the raw GSV may not be so good. Thus, we apply RFDA-based projection method on the raw GSV, and find that this projection method can significantly improve the performance of the raw GSV, in both telephone session identification and recording device identification tasks.
ISBN: 9781509061815
DOI: 10.1109/IJCNN.2017.7965921
Appears in Collections:Conference Paper

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