Aplicación de RNA y HMM a la Verificación Automática de Locutor
(Application of ANN and HMM to Automatic Speaker Verification)
Federico Leonardo Alegre (firstname.lastname@example.org)
Departamento de Matemática Universidad Nacional del Comahue (UNCo), Neuquén, Argentina
This paper appears in: Revista IEEE América Latina
Publication Date: Sept. 2007
Volume: 5, Issue: 5
This paper describes the development and implementation of a speaker verification system, applied as a telephony security tool. This software was made using two of the most popular techniques in the commercial recognition systems, techniques based in Hidden Markov Models (HMM) and Artificial Neural Networks (ANN) theory. First of all, the qualities of the system were chosen. Then, the different parts that make up the verification system (speech characteristics extraction, pattern recognition, decision rules, among others) were developed. Therefore, the system was tested in order to adjust design parameters and to evaluate its performance. Finally the verification system took part in a interactive answering machine, using a Intel Dialogic ProLine/2V telephony card for this purpose.
speaker verification, Artificial Neural Networks, Hidden Markov Models, text-prompted
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