Research Article
Voice Identification Using Neural Network And Mel Frequency Cepstrum Coefficients
@INPROCEEDINGS{10.4108/eai.18-7-2019.2288519, author={Corianti GMS and Fahmi Fahmi and Maksum Pinem and Sihar P. Panjaitan and Suherman Suherman}, title={Voice Identification Using Neural Network And Mel Frequency Cepstrum Coefficients}, proceedings={Proceedings of The 2nd International Conference On Advance And Scientific Innovation, ICASI 2019, 18 July, Banda Aceh, Indonesia}, publisher={EAI}, proceedings_a={ICASI}, year={2019}, month={11}, keywords={voice recognition mel frequency cestrum coefficients artificial neural network}, doi={10.4108/eai.18-7-2019.2288519} }- Corianti GMS
Fahmi Fahmi
Maksum Pinem
Sihar P. Panjaitan
Suherman Suherman
Year: 2019
Voice Identification Using Neural Network And Mel Frequency Cepstrum Coefficients
ICASI
EAI
DOI: 10.4108/eai.18-7-2019.2288519
Abstract
Voice as a communication media for human and computer communication is developed by using voice recognition/identification technology. One of its applications is differentiate between male and female voices. Some speech recognition research have been proposed in disseminating male and female voices, this paper performs male and female voice extraction by using Mel Frequency Cestrum Coefficients (MFCC) as the characteristic vector in back propagation artificial neural network (ANN). The weight change cycle or EPOCH (Exponential Decay) is used to initialize male and female voice identification by using multiple recorded voices. As results, the female voice identification is better than of male with error less than 1.
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