Selection of the Best Wavelet Packet Nodes Based on Mutual Information for Speaker Identification

Authors:
Rafael Fernández;Ana Montalvo;José R. Calvo;Gabriel Hernández
Affiliations:
Advanced Technologies Application Center, Havana, Cuba;Advanced Technologies Application Center, Havana, Cuba;Advanced Technologies Application Center, Havana, Cuba;Advanced Technologies Application Center, Havana, Cuba
Venue:
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Year:
2008

Citing 3
Cited 1

Elements of information theory

Elements of information theory
AHUMADA: A large speech corpus in Spanish for speaker characterization and identification

Speech Communication - Speaker recognition and its commercial and forensic applications
Feature Selection Based on Mutual Information: Criteria of Max-Dependency, Max-Relevance, and Min-Redundancy

IEEE Transactions on Pattern Analysis and Machine Intelligence

Feature Selection Based on Information Theory for Speaker Verification

CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

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Abstract

The analysis of the speech signal using wavelet packet trees (WPT) is a very flexible tool, capable of effectively manipulate the frequency subbands thanks to the orthonormal bases it provides. Here, dimension reduction becomes very important since the number of subbands grows exponentially with the level of decomposition, and their discriminative relevancy is different, which leads to different resolution for each one. A method based on mutual information is proposed in order to keep as much discriminative information as possible and the less amount of redundant information.