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Design of a Voice Activity Detection Algorithm based on Logarithmic Signal Energy

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dc.contributor.author Özaydın, Selma
dc.date.accessioned 2024-03-12T11:30:36Z
dc.date.available 2024-03-12T11:30:36Z
dc.date.issued 2022
dc.identifier.citation Özaydın, Selma. "Design of a Voice Activity Detection Algorithm based on Logarithmic Signal Energy", International Conference on Electrical and Computing Technologies and Applications (ICECTA), pp. 19-22, 2022. tr_TR
dc.identifier.uri http://hdl.handle.net/20.500.12416/7541
dc.description.abstract This article presents a new method for calculating the signal energies of speech segments in voice activity detection algorithms. In the study, the µ-law signal compression method is adapted to calculate short-term signal energies. A simple voice activity detection (VAD) algorithm is designed to demonstrate the effectiveness of the proposed method. The same VAD algorithm was also run with two different conventional energy calculation formulas and the performance of each VAD was evaluated using time-domain short-time energy features. The G729 standard VAD algorithm was also used for performance comparison. During the test of the analyzed detectors, many kinds of input speech signals with various types of background environmental noise, such as restaurants, vehicles, and streets, were tested. Using the new energy calculation method, the VAD detector has improved detection accuracy compared to VAD detectors based on the other two energy methods and was able to effectively identify voice-active regions even in noisy conditions at low SNR levels. The results revealed that the VAD detector designed with the proposed new energy calculation formula outperforms traditional energy-based voice activity detection methods and provides noticeable increases in detection rate even under adverse conditions. tr_TR
dc.language.iso eng tr_TR
dc.publisher IEEE tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Voice Activity Detection tr_TR
dc.subject Speech Analysis tr_TR
dc.subject Endpoint Detection tr_TR
dc.subject Feature Analysis tr_TR
dc.subject Signal Energy Calculation tr_TR
dc.title Design of a Voice Activity Detection Algorithm based on Logarithmic Signal Energy tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal International Conference on Electrical and Computing Technologies and Applications (ICECTA) tr_TR
dc.contributor.authorID 253019 tr_TR
dc.identifier.startpage 19 tr_TR
dc.identifier.endpage 22 tr_TR
dc.contributor.department Çankaya Üniversitesi, Meslek Yüksek Okulu, Bilgisayar Programcılığı Bölümü tr_TR


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