A Tutorial on Text-Independent Speaker Verification
Name
1687-6180-2004-101962.pdf
Size
1.12 MB
Format
Adobe PDF
Checksum (MD5)
7b9aba54494f89177a65f9e6ccca1d8b
Author(s)
Bimbot, Frederic
Bonastre, Jean-François
Fredouille, Corinne
Gravier, Guillaume
Magrin-Chagnolleau, Ivan
Meignier, Sylvain
Merlin, Teva
Javier, Ortega-Garcia
Petrovska-Delacretaz, Dijana
Reynolds, Douglas A.
Date Issued
April 2004
Journal
EURASIP Journal on Advances in Signal Processing
Publisher
Springer
Citation
Bimbot, Frédéric et al. “A Tutorial on Text-Independent Speaker Verification.” EURASIP Journal on Advances in Signal Processing 2004.4 (2004): 430-451. Web.
Version
Author's final manuscript
Abstract
This paper presents an overview of a state-of-the-art text-independent speaker verification system. First, an introduction proposes a modular scheme of the training and test phases of a speaker verification system. Then, the most commonly speech parameterization used in speaker verification, namely, cepstral analysis, is detailed. Gaussian mixture modeling, which is the speaker modeling technique used in most systems, is then explained. A few speaker modeling alternatives, namely, neural networks and support vector machines, are mentioned. Normalization of scores is then explained, as this is a very important step to deal with real-world data. The evaluation of a speaker verification system is then detailed, and the detection error trade-off (DET) curve is explained. Several extensions of speaker verification are then enumerated, including speaker tracking and segmentation by speakers. Then, some applications of speaker verification are proposed, including on-site applications, remote applications, applications relative to structuring audio information, and games. Issues concerning the forensic area are then recalled, as we believe it is very important to inform people about the actual performance and limitations of speaker verification systems. This paper concludes by giving a few research trends in speaker verification for the next couple of years.
MIT Department
Lincoln Laboratory
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1155/S1110865704310024
