Fake Voice Detection: A Hybrid CNN-LSTM Based Deep Learning Approach

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dc.contributor.authorOyucu, Saadin
dc.contributor.authorÇelimli, Derya Betül Ünsal
dc.contributor.authorAksöz, Ahmet
dc.date.accessioned2025-05-04T16:41:58Z
dc.date.available2025-05-04T16:41:58Z
dc.date.issued2024
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description8th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2024 -- 7 November 2024 through 9 November 2024 -- Ankara -- 204563
dc.description.abstractThis study focuses on developing and evaluating a hybrid Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) based deep learning model for detecting fake voice recordings. The proposed model addresses the critical issue of artificial intelligence-generated speech mimicking human voices, which can potentially be used for malicious purposes, thereby endangering individuals' privacy and safety. A comprehensive dataset comprising 5,889 real and 5,889 fake voice samples was utilized for this research. The dataset underwent rigorous preprocessing, including segmentation into fixed-length windows and normalization. The hybrid CNN-LSTM model was then trained and validated systematically involving exploratory data analysis and extensive hyperparameter tuning. The experimental results demonstrated that the proposed model achieved an accuracy of 99.2%, an F1 score of 99.2%, a recall of 99.4%, and a precision of 99.0%, indicating its robust performance in distinguishing between real and fake voices. The findings underscore the potential of the hybrid CNN-LSTM model as a powerful tool for safeguarding digital communications against the growing threat of fake voices. © 2024 IEEE.
dc.identifier.doi10.1109/ISMSIT63511.2024.10757293
dc.identifier.isbn979-835035442-3
dc.identifier.scopus2-s2.0-85213320665
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/ISMSIT63511.2024.10757293
dc.identifier.urihttps://hdl.handle.net/20.500.12418/35016
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofISMSIT 2024 - 8th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250504
dc.subjectaudio forensics
dc.subjectconvolutional neural network (CNN)
dc.subjectfake voice detection
dc.subjectlong short-term memory (LSTM)
dc.titleFake Voice Detection: A Hybrid CNN-LSTM Based Deep Learning Approach
dc.typeConference Object

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