Speaker identification based on artificial neural networks. Case study: the Polish vowel (pilot study)

• Autorzy: Salapa K. , Trawińska A. , Roterman I. , Tadeusiewicz R.
• Języki publikacji: EN

Abstrakty

EN

Current statistical methods and technologies used for speaker identification via dynamic formant frequency often involve classic multivariate analyses that must meet a number of criteria in order to be considered trustworthy. The authors propose more advanced classification techniques, including artificial neural networks. Owing to iterative learning algorithms, neural networks can be trained to detect highly complex, nonlinear relations hidden in input data. This study specifically considers feed-forward multilayer perceptron and radial basic function network models. The investigation involves an analysis of the Polish vowel (stressed or unstressed) in selected contexts described by the four lowest formant frequencies. Results indicate high accuracy of neural networks as a speaker identification tool reaching up to 100%. In addition, the authors have determined that the accuracy of classification is similar when based on a single context to when input data are aggregated over several different contexts.

Słowa kluczowe

EN

artificial neural networks; data mining; formant frequencies; speaker identification; voice comparison

• Wydawca: Uniwersytet Jagielloński - Collegium Medicum ; Index Copernicus Sp. z o.o.
• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2014
• Tom: Vol. 10, no. 2
• Strony: 91--99
• Opis fizyczny: Bibliogr. 33 poz., wykr.

Twórcy

autor

Salapa K.

• Department of Bioinformatics and Telemedicine, Jagiellonian University Medical College, Cracow, Poland

autor

Trawińska A.

• Institute of Forensic Research, Cracow, Poland

autor

Roterman I.

• Department of Bioinformatics and Telemedicine, Jagiellonian University Medical College, Cracow, Poland

autor

Tadeusiewicz R.

• Department of Automatics and Biomedical Engineering, AGH University of Science and Technology, Cracow, Poland

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