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Multi Lingual Speaker Identification on Foreign Languages Using Artificial Neural Network

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Executive Summary

Based on the Back Propagation Algorithm, this paper portrait a method for speaker identification in multiple foreign languages. In order to identify speaker, the complete process goes through recording of the speech utterances of different speakers in multiple foreign languages, features extraction, data clustering and system training. In order to realize the purpose, a database has been prepared which contains one sentence in 8 different international languages i.e. Catalan, French, Finnish, Italian, Portuguese, Indonesian, Hindi, English spoken by 19 distinct speakers, both male and female, in each language. With total size of 760 speech utterances, the average performance of the system is 95.657%

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