Deepfake Audio Detection via MFCC Features Using Machine Learning-Reference-Cited by-同舟云学术

Deepfake Audio Detection via MFCC Features Using Machine Learning

Published:2022 Issue: Volume:10 Page:134018-134028
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Hamza Ameer¹,Javed Abdul Rehman Rehman²^ORCID,Iqbal Farkhund³^ORCID,Kryvinska Natalia⁴^ORCID,Almadhor Ahmad S.⁵^ORCID,Jalil Zunera²^ORCID,Borghol Rouba⁶^ORCID

Affiliation:

1. Faculty of Computing and AI, Air University, Islamabad, Pakistan

2. Department of Cyber Security, Air University, Islamabad, Pakistan

3. College of Technological Innovation, Zayed University, Abu Dhabi, United Arab Emirates

4. Department of Information Systems, Faculty of Management, Comenius University in Bratislava, Bratislava, Slovakia

5. College of Computer and Information Sciences, Jouf University, Sakaka, Saudi Arabia

6. Rochester Institute of Technology of Dubai, Dubai, United Arab Emirates

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09996362.pdf?arnumber=9996362

Reference36 articles.

1. The ASVspoof 2017 Challenge: Assessing the Limits of Replay Spoofing Attack Detection

2. Probabilistic forecasting with temporal convolutional neural network

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