Statistical Study for Enhancing the MFCC Algorithm for Real-World and Highly Noisy Environments in Voiceprint Extraction

dc.contributor.author	Asmaa Barakat
dc.contributor.author	Nada Abu Nokra
dc.contributor.author	Abdul Rahman Hussian
dc.date.accessioned	2026-01-02T12:08:56Z
dc.date.issued	2024-02-13
dc.description.abstract	The aim of this study is to present a novel exploration for obtaining an enhanced version of the MFCC algorithm to capitalize on its superior quality in sound analysis and voiceprint extraction. The objective is to overcome challenges in using the MFCC algorithm in real-world and highly noisy environments, where speech is susceptible to noise and interference in natural settings. This, in turn, diminishes the performance of the MFCC-based system in real-world applications
dc.format	application/pdf
dc.identifier.uri	https://geniusjournals.org/index.php/ejet/article/view/5641
dc.identifier.uri	https://asianeducationindex.com/handle/123456789/78806
dc.language.iso	eng
dc.publisher	Genius Journals
dc.relation	https://geniusjournals.org/index.php/ejet/article/view/5641/4731
dc.rights	https://creativecommons.org/licenses/by-nc/4.0
dc.source	Eurasian Journal of Engineering and Technology; Vol. 27 (2024): EJET; 10-23
dc.source	2795-7640
dc.subject	Noise Reduction
dc.subject	Voiceprint
dc.subject	MFCC Algorithm
dc.title	Statistical Study for Enhancing the MFCC Algorithm for Real-World and Highly Noisy Environments in Voiceprint Extraction
dc.type	info:eu-repo/semantics/article
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	Peer-reviewed Article

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