Effect of Reverberation Phenomena on Text- independent Speaker Recognition Based Deep Learning
Abd El-Moneim, S., Hassan, S., Sedik, A., Nassar, M., Dessouky, M., Ismail, N., El-Fishawy, A., El-Banby, G., Khalaf, A., Abd El-Samie, F. (2019). Effect of Reverberation Phenomena on Text- independent Speaker Recognition Based Deep Learning. EKB Journal Management System, 28(ICEEM2019-Special Issue), 19-23. doi: 10.21608/mjeer.2019.76669
Samia Abd El-Moneim; Shaimaa E. A. Aziz Hassan; Ahmed Sedik; M. A. Nassar; Moawd I. Dessouky; Nabil A. Ismail; Adel S. El-Fishawy; Ghada M. El-Banby; Ashraf A. M. Khalaf; Fathi I. Abd El-Samie. "Effect of Reverberation Phenomena on Text- independent Speaker Recognition Based Deep Learning". EKB Journal Management System, 28, ICEEM2019-Special Issue, 2019, 19-23. doi: 10.21608/mjeer.2019.76669
Abd El-Moneim, S., Hassan, S., Sedik, A., Nassar, M., Dessouky, M., Ismail, N., El-Fishawy, A., El-Banby, G., Khalaf, A., Abd El-Samie, F. (2019). 'Effect of Reverberation Phenomena on Text- independent Speaker Recognition Based Deep Learning', EKB Journal Management System, 28(ICEEM2019-Special Issue), pp. 19-23. doi: 10.21608/mjeer.2019.76669
Abd El-Moneim, S., Hassan, S., Sedik, A., Nassar, M., Dessouky, M., Ismail, N., El-Fishawy, A., El-Banby, G., Khalaf, A., Abd El-Samie, F. Effect of Reverberation Phenomena on Text- independent Speaker Recognition Based Deep Learning. EKB Journal Management System, 2019; 28(ICEEM2019-Special Issue): 19-23. doi: 10.21608/mjeer.2019.76669

Effect of Reverberation Phenomena on Text- independent Speaker Recognition Based Deep Learning

Menoufia Journal of Electronic Engineering Research
Article 25, Volume 28, ICEEM2019-Special Issue, 2019, Page 19-23  XML
Document Type: Original Article
DOI: 10.21608/mjeer.2019.76669
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Authors
Samia Abd El-Moneim1; Shaimaa E. A. Aziz Hassan2; Ahmed Sedik3; M. A. Nassar2; Moawd I. Dessouky4; Nabil A. Ismail2; Adel S. El-Fishawy2; Ghada M. El-Banby5; Ashraf A. M. Khalaf6; Fathi I. Abd El-Samie2
1Communications and Electronics Department Tanta High Institute of Engineering and Technology Tanta, Egypt
2Communications and Electronics Department Faculty of Electronic Engineering,Manoufia University: Menouf, Egypt
3Department of Robotics and intelligent machines, Faculty of artificial intelligents Kafrelsheikh University: Egypt
4Communications and Electronics Department Faculty of Electronic Engineering,Manoufia University: Menouf, Egypt,
5Automatic Control Department Faculty of Electronic Engineering,Manoufia University: Menouf, Egypt
6Electrical engineering Department Faculty of Engineering,Minia University: Egypt
Abstract
Speaker recognition is one of many biometric authentications, due to its high importance in many applications of security considerations and telecommunications. The main aspiration of speaker recognition system is to know who is speaking depending on voice characteristics. Many current researches focuses on text-dependent speaker recognition which has a pre-knowledge of what utterance the speaker will say. In this paper text-independent speaker recognition system is used, where no prior knowledge is accessible in the context of the speakers’ utterances for all stages. A Convolutional Neural Network (CNN) based feature extraction is extended to a text-independent Speaker recognition task. Also the effect of reverberation on speaker recognition is addressed. All the speech signals are converted into images by obtaining their spectrograms. A proposed CNN model is presented to enhance the performance of the system in case of a reverberant signal. It depends on image processing concepts, and hence spectrograms of signals are used. The proposed model is compared with a conventional benchmark model. The performance of the recognition system is measured by the recognition rate in the case of clean and reverberant data.
Keywords
Speaker recognition; CNN; reverberation; spectrogram; recognition rate
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