Speaker identification in mismatch training and testing conditions

Speaker identification in mismatch training and testing conditions

This paper presents an exhaustive study about the robustness of several parameterizations, with a new database specially acquired for the purpose of this study. This database includes the following variations: different recording sessions (including telephonic and microphonic recordings), recording...

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Bibliographic Details
Published in:2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100) Vol. 2; pp. II1181 - II1184 vol.2
Main Authors: Alonso-Martinez, C., Faundez-Zanuy, M.
Format: Conference Proceeding
Language:English
Published: IEEE 2000
Subjects:
CD recording
ISDN
Microphones
Natural languages
Robustness
Speaker recognition
Speech
Testing
Vector quantization
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Summary:This paper presents an exhaustive study about the robustness of several parameterizations, with a new database specially acquired for the purpose of this study. This database includes the following variations: different recording sessions (including telephonic and microphonic recordings), recording rooms, and languages (it has been obtained from a bilingual set of speakers). This study has been performed with two identification algorithms (vector quantization and covariance matrices) and reveals that the combination of several parameterizations can improve the robustness in all the scenarios.
ISBN:9780780362932
0780362934
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2000.859176