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Title: Noise robust speaker verification via the fusion of SNR-independent and SNR-dependent PLDA
Authors: Pang, X 
Mak, MW 
Issue Date: Dec-2015
Source: International journal of speech technology, Dec. 2015, v. 18, no. 4, p. 633-648
Abstract: While i-vectors with probabilistic linear discriminant analysis (PLDA) can achieve state-of-the-art performance in speaker verification, the mismatch caused by acoustic noise remains a key factor affecting system performance. In this paper, a fusion system that combines a multi-condition signal-to-noise ratio (SNR)-independent PLDA model and a mixture of SNR-dependent PLDA models is proposed to make speaker verification systems more noise robust. First, the whole range of SNR that a verification system is expected to operate is divided into several narrow ranges. Then, a set of SNR-dependent PLDA models, one for each narrow SNR range, are trained. During verification, the SNR of the test utterance is used to determine which of the SNR-dependent PLDA models is used for scoring. To further enhance performance, the SNR-dependent and SNR-independent models are fused using linear and logistic regression fusion. The performance of the fusion system and the SNR-dependent system is evaluated on the NIST 2012 speaker recognition evaluation for both noisy and clean conditions. Results show that a mixture of SNR-dependent PLDA models perform better in both clean and noisy conditions. It was also found that the fusion system is more robust than the conventional i-vector/PLDA systems under noisy conditions.
Keywords: Fusion
Noise robustness
Probabilistic LDA
Speaker verification
Publisher: Springer
Journal: International journal of speech technology 
ISSN: 1381-2416
DOI: 10.1007/s10772-015-9310-8
Rights: © Springer Science+Business Media New York 2015
This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at:
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