Tactical speaker recognition using feature and classifier fusion

Laurie H. Fenstermacher; Douglas Smith

doi:10.1117/12.169995

2 March 1994 Tactical speaker recognition using feature and classifier fusion

Laurie H. Fenstermacher, Douglas Smith

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.

Citation Download Citation

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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