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Title: SNR-invariant PLDA modeling in nonparametric subspace for robust speaker verification
Authors: Li, N 
Mak, MW 
Issue Date: Oct-2015
Source: IEEE transactions on audio, speech and language processing, Oct. 2015, v. 23, no. 10, p. 1648-1659
Abstract: While i-vector/PLDA framework has achieved great success, its performance still degrades dramatically under noisy conditions. To compensate for the variability of i-vectors caused by different levels of background noise, this paper proposes an SNR-invariant PLDA framework for robust speaker verification. First, nonparametric feature analysis (NFA) is employed to suppress intra-speaker variation and emphasize the discriminative information inherited in the boundaries between speakers in the i-vector space. Then, in the NFA-projected subspace, SNR-invariant PLDA is applied to separate the SNR-specific information from speaker-specific information using an identity factor and an SNR factor. Accordingly, a projected i-vector in the NFA subspace can be represented as a linear combination of three components: speaker, SNR, and channel. During verification, the variability due to SNR and channels are integrated out when computing the marginal likelihood ratio. Experiments based on NIST 2012 SRE show that the proposed framework achieves superior performance when compared with the conventional PLDA and SNR-dependent mixture of PLDA.
Keywords: i-vector
Nonparametric feature analysis
Probabilistic linear discriminant analysis (PLDA)
Speaker verification
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on audio, speech and language processing 
ISSN: 1558-7916
EISSN: 1558-7924
DOI: 10.1109/TASLP.2015.2442757
Rights: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works.
The following publication Li, N., & Mak, M. W. (2015). SNR-invariant PLDA modeling in nonparametric subspace for robust speaker verification. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 23(10), 1648-1659 iis available at
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