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- W70092504 abstract "Today the law enforcement agencies use automatic biometric identification systems, which utilize human biometric features in order to identify criminals.This thesis was correlated with the objective of forensic laboratories. Hence, a data base of human speech samples and a speaker identification system were developed using the Matlab software. The scope was to increase, in future, the number of the data base samples and to combine features, comparison and classification methods. The system is full automatic, open set, text depended and text independent.From every speech sample, the mel frequency coefficients using the Malcolm Slaney Auditory Toolbox was extracted. The comparison of the speech samples was implemented with two methods: 3M and WW-Test which are based on the graph theory. Finally, the K-NN classifier was used for the classification of the speech samples.From the system evaluation, we conclude that the feature extraction method has the main effect on the system performance. The combination of several features, comparison and classification methods improves the reliability of the system." @default.
- W70092504 created "2016-06-24" @default.
- W70092504 creator A5078369629 @default.
- W70092504 date "2009-04-06" @default.
- W70092504 modified "2023-09-27" @default.
- W70092504 title "Εγκληματολογική αναγνώριση ομιλητή" @default.
- W70092504 hasPublicationYear "2009" @default.
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