Various Speaker Recognition Techniques Using a Special Nonlinear Metric

Authors:
Tudor Barbu;Mihaela Costin
Affiliations:
Institute for Computer Sciences of the Romanian Academy, Iasi branch, , Romania;Institute for Computer Sciences of the Romanian Academy, Iasi branch, , Romania
Venue:
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part III
Year:
2008

Citing 2
Cited 1

Survey of the state of the art in human language technology

Survey of the state of the art in human language technology
Pattern Classification (2nd Edition)

Pattern Classification (2nd Edition)

Images revealing useful clues on Romanian vowels spectrograms

WORLD-EDU'12/CIT'12 Proceedings of the 6th international conference on Communications and Information Technology, and Proceedings of the 3rd World conference on Education and Educational Technologies

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Abstract

In this paper we compare voice recognition techniques using a special nonlinear metric. We describe text-dependent and text-independent speaker recognition methods based on a mel-cepstral analysis in the feature extraction stage and a supervised classification. The Hausdorff-based metric proposed by us is able to measure the distance between different sized speech feature vectors resulted from the mel-cepstral featuring process. Then, a minimum mean distance classifier uses this new distance to identify the speakers.