This book presents AUDI-FAKE as a unified approach to intelligent audio deepfake detection using pretrained and foundation-model-based representations. It shows why no single pretrained model captures all the cues needed for reliable detection in diverse, realistic conditions and demonstrates how speech encoders, multilingual models, and audio-tagging models can be combined to improve performance. The book offers a progressive treatment of the subject, covering the foundations of audio deepfake detection, benchmark datasets, pretrained models, and conventional detection methods, while examining important and underexplored detection settings. It is a useful resource for researchers and advanced students working in speech, audio, and multimodal machine learning.

Mohd Mujtaba Akhtar holds an M.Tech. in Computer Science and Engineering from UNSIET, Veer Bahadur Singh Purvanchal University, Jaunpur, India. His research focuses on representation learning, speech and audio processing, multimodal and audiovisual learning, structured latent space design, computational audio pattern recognition, and foundation model adaptation. He has published research on advanced machine learning and deep learning for speech and audio understanding, with particular emphasis on deepfake detection, paralinguistic processing, multilingual speech analysis, and robust learning frameworks. His work has been presented at leading international venues, including ACL 2026, EACL 2026, IJCNLP-AACL 2025, INTERSPEECH 2025, ICASSP 2025, EUSIPCO 2025, APSIPA ASC 2025, ISDIA 2026, and ICSADL 2026, and in Computer & Electrical Engineering. His research reflects sustained engagement with audio deepfake detection, speech emotion recognition, source attribution, multilingual speech modeling, and multimodal learning. His paper presented at EACL 2026 received the Social Impact Award, and his work presented at ISDIA 2026 received the Best Paper Award. He also received a travel grant to attend and present his work at EUSIPCO 2025.

Vikrant Bhateja is an Associate Professor in the Department of Electronics Engineering, Faculty of Engineering and Technology, UNSIET, Veer Bahadur Singh Purvanchal University, Jaunpur, Uttar Pradesh, India. He also serves as Head of Computer Science Engineering and Information Technology at the same university. He holds a doctorate in Electronics and Communication Engineering with specialization in biomedical imaging and has 23 years of academic teaching experience. He has authored around 195 publications in international conferences, journals, and book chapters, including 45 papers in SCIE-indexed journals. One of his papers published in Review of Scientific Instruments was selected as the Editor's Choice Paper of the Issue in 2016. Among his international conference publications, five papers have received Best Paper Awards. He has guided many B.Tech. students whose final-year projects received support from the UP Council for Science and Technology. He received the Academic Excellence Award for 2024-25 from the Hon'ble Governor of Uttar Pradesh in the UP State-University category. He has chaired or co-chaired more than 65 international conferences in India and abroad as Publication Chair or TPC Chair and has edited 75 Springer Nature book volumes as corresponding editor, co-editor, or author. He has delivered nearly 30 keynote and invited talks at international conferences and in ATAL, TEQIP, and other AICTE-sponsored FDPs and STTPs. He served as Editor-in-Chief of IGI Global's International Journal of Natural Computing and Research from 2017 to 2022 and has been a guest editor for journals including Elsevier's Measurement and Springer's Evolutionary Intelligence. He is a Senior Member of IEEE and a Life Member of CSI. His published research has a current Google Scholar h-index of 38.