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Support vector machines using GMM supervectors for speaker verification
Abstract
Gaussian mixture models (GMMs) have proven extremely successful for text-independent speaker recognition. The standard training method for GMM models is to use MAP adaptation of the means of the mixture components based on speech from a target speaker. Recent methods in compensation for speaker and channel variability have proposed the idea of stacking the means of the GMM model to form a GMM mean supervector. We examine the idea of using the GMM supervector in a support vector machine (SVM) classifier. We propose two new SVM kernels based on distance metrics between GMM models. We show that these SVM kernels produce excellent classification accuracy in a NIST speaker recognition evaluation task.
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Cited by
Spoofing and countermeasures for speaker verification: A survey
Wu, Z., Evans, N., Kinnunen, T., Yamagishi, J., Alegre, F., & Li, H. (2015) · Speech Communication · doi:10.1016/j.specom.2014.10.005 · Cited by 601
EmotionSense: a mobile phones based adaptive platform for experimental social psychology research
Rachuri, K. K., Musolesi, M., Mascolo, C., Rentfrow, P. J., Longworth, C., & Aucinas, A. (2010) · Proceedings of the 12th ACM international conference on Ubiquitous computing · doi:10.1145/1864349.1864393 · Cited by 508
A review of biometric technology along with trends and prospects
Unar, J. A., Seng, W. C., & Abbasi, A. (2014) · Pattern Recognition · doi:10.1016/j.patcog.2014.01.016 · Cited by 404
Speaker recognition based on deep learning: An overview
Bai, Z., & Zhang, X.-L. (2021) · Neural Networks · doi:10.1016/j.neunet.2021.03.004 · Cited by 386
An Overview of Speaker Identification: Accuracy and Robustness Issues
Togneri, R., & Pullella, D. (2011) · IEEE Circuits and Systems Magazine · doi:10.1109/mcas.2011.941079 · Cited by 263
Metadata
- Authors
- Campbell, W. M., Sturim, D. E., & Reynolds, D. A.
- Venue
- IEEE Signal Processing Letters
- Published
- 2006-05
- Volume
- 13
- Issue
- 5
- Pages
- 308-311
- ISSN
- 1070-9908 (ISSN-L)
- OpenAlex
- W2147147599
- Cited by
- 1,013
- References
- 0
- FWCI
- 50.14
- Type
- journal article
- Language
- en
- Open access
- closed
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- Campbell, W. M., Sturim, D. E., & Reynolds, D. A. (2006). Support vector machines using GMM supervectors for speaker verification. IEEE Signal Processing Letters. https://doi.org/10.1109/lsp.2006.870086
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