Speakers Recognition Based On Convolution

Alsaif, Khalil Ibrahim; Saeed, Nagham; Altoni, Esraa Abd Alsalm

doi:10.33899/edusj.2020.172816

	Speakers Recognition Based On Convolution
Journal of Education and Science
Article 22, Volume 29, Issue 1, 2020, Pages 293-309 PDF (861.92 K)
Document Type: Research Paper
DOI: 10.33899/edusj.2020.172816
Authors
Khalil Ibrahim Alsaif^* ¹; Nagham Saeed; esraa abd alsalm altoni²
¹Computer Science Department- College of computer science and Mathematics- University of Mosul-Mosul-Iraq
²computer science ,education pure science ,Mosul , Iraq
Abstract
In this research, the important features of recognizing speakers' identity by extracting features of speakers voices are used. Voice is considered one of the vital factors adopted algorithm on samples of speakers' voices has been implemented by recording the voice, saving it on a file of the type wav. The voice is treated by using Hamming function to reduce error ratio. Feature of the voice samples have been extracted by taking the spectrum value of the sound signal of all the speakers. Two methods have been used (Ecledian distance and correlation factor) for comparing core of the convolution of the sample of speaker test (a training sample which is being recorded another time) and all the speakers samples who have already been saved on the data base. Applying the algorithm on different voices, ratio of error was very small while matching has increased by the increasing number of speaker. The algorithm has been implemented using mathlab.
Keywords
convolution algorithm; Hamming function; Ecledian distance and correlation factor

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