Tactical speaker recognition using feature and classifier fusion

Laurie H. Fenstermacher; Douglas Smith

doi:10.1117/12.169995

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2 March 1994 Tactical speaker recognition using feature and classifier fusion

Laurie H. Fenstermacher; Douglas Smith

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Proceedings Volume 2243, Applications of Artificial Neural Networks V; (1994) https://doi.org/10.1117/12.169995
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

Tactical communications are inherently short and exhibit a great deal of channel variability. A novel speaker recognition technique was developed which uses on-line training to circumvent the need for excessive speaker or channel modeling. The technique incorporates both feature set fusion and classifier fusion. Separate classifiers are trained for each feature set: liftered LPC cepstra, RASTA liftered cepstra concomitant with delta cepstra. For each classifier, the results of the individual (feature) classifiers are adjudicated to rank the speakers. A final step adjudicates the results of different classifiers to determine the correct speaker.

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Laurie H. Fenstermacher and Douglas Smith "Tactical speaker recognition using feature and classifier fusion", Proc. SPIE 2243, Applications of Artificial Neural Networks V, (2 March 1994); https://doi.org/10.1117/12.169995

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KEYWORDS

Speaker recognition

Databases

Feature extraction

Autoregressive models

Adaptive control

Composites

Control systems

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