Faculty of Information Technology, BUT

Publication Details

Towards Noise-Robust Speaker Recognition Using Probabilistic Linear Discriminant Analysis

LEI Yun, BURGET Lukáš, FERRER Luciana, GRACIARENA Martin and SCHEFFER Nicolas. Towards Noise-Robust Speaker Recognition Using Probabilistic Linear Discriminant Analysis. In: Proc. International Conference on Acoustics, Speech, and Signal P. Kyoto: IEEE Signal Processing Society, 2012, pp. 4253-4256. ISBN 978-1-4673-0044-5.
Czech title
Posun k rozpoznávání mluvčího robustnímu vůči šumu pomocí pravděpodobnostní lineární diskriminační analýzy
Type
conference paper
Language
english
Authors
Lei Yun (SRI)
Burget Lukáš, doc. Ing., Ph.D. (DCGM FIT BUT)
Ferrer Luciana (SRI)
Graciarena Martin (SRI)
Scheffer Nicolas (SRI)
URL
Keywords
Speaker Recognition, noise, robustness, i-vector, PLDA
Abstract
We show results on a newly designed noisy corpus for speaker recognition where real recordings of babble noise were added to original NIST SRE clean speech data.
Annotation
This work addresses the problem of speaker verification where additive noise is present in the enrollment and testing utterances. We show how the current state-of-the-art framework can be effectively used to mitigate this effect. We first look at the degradation a standard speaker verification system is subjected to when presented with noisy speech waveforms. We designed and generated a corpus with noisy conditions, based on the NIST SRE 2008 and 2010 data, built using open-source tools and freely available noise samples. We then show how adding noisy training data in the current i-vectorbased approach followed by probabilistic linear discriminant analysis (PLDA) can bring significant gains in accuracy at various signal-to-noise ratio (SNR) levels. We demonstrate that this improvement is not feature-specific as we present positive results for three disparate sets of features: standard mel frequency cepstral coefficients, prosodic polynomial coefficients and maximum likelihood linear regression (MLLR) transforms.
Published
2012
Pages
4253-4256
Proceedings
Proc. International Conference on Acoustics, Speech, and Signal P
Conference
The 37th International Conference on Acoustics, Speech, and Signal Processing, Kyoto, JP
ISBN
978-1-4673-0044-5
Publisher
IEEE Signal Processing Society
Place
Kyoto, JP
DOI
BibTeX
@INPROCEEDINGS{FITPUB9996,
   author = "Yun Lei and Luk\'{a}\v{s} Burget and Luciana Ferrer and Martin Graciarena and Nicolas Scheffer",
   title = "Towards Noise-Robust Speaker Recognition Using Probabilistic Linear Discriminant Analysis",
   pages = "4253--4256",
   booktitle = "Proc. International Conference on Acoustics, Speech, and Signal P",
   year = 2012,
   location = "Kyoto, JP",
   publisher = "IEEE Signal Processing Society",
   ISBN = "978-1-4673-0044-5",
   doi = "10.1109/ICASSP.2012.6288858",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/9996"
}
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