Concept

Audio deepfake

An audio deepfake (also known as voice cloning) is a type of artificial intelligence used to create convincing speech sentences that sound like specific people saying things they did not say. This technology was initially developed for various applications to improve human life. For example, it can be used to produce audiobooks, and also to help people who have lost their voices (due to throat disease or other medical problems) to get them back. Commercially, it has opened the door to several opportunities. This technology can also create more personalized digital assistants and natural-sounding text-to-speech as well as speech translation services. Audio deepfakes, recently called audio manipulations, are becoming widely accessible using simple mobile devices or personal computers. These tools have also been used to spread misinformation using audio. This has led to cybersecurity concerns among the global public about the side effects of using audio deepfakes, including its possible role in disseminating misinformation and disinformation in audio-based social media platforms. People can use them as a logical access voice spoofing technique, where they can be used to manipulate public opinion for propaganda, defamation, or terrorism. Vast amounts of voice recordings are daily transmitted over the Internet, and spoofing detection is challenging. Audio deepfake attackers have targeted individuals and organizations, including politicians and governments. In early 2020, some scammers used artificial intelligence-based software to impersonate the voice of a CEO to authorize a money transfer of about $35 million through a phone call. According to a 2023 global McAfee survey, one person in ten reported having been targeted by an AI voice cloning scam; 77% of these targets reported losing money to the scam. Audio deepfakes could also pose a danger to voice ID systems currently deployed to financial consumers. Audio deepfakes can be divided into three different categories: Replay-based deepfakes are malicious works that aim to reproduce a recording of the interlocutor's voice.

Official source

https://en.wikipedia.org/wiki/Audio_deepfake

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Related courses (1)

EE-556: Mathematics of data: from theory to computation

This course provides an overview of key advances in continuous optimization and statistical analysis for machine learning. We review recent learning formulations and models as well as their guarantees

Related lectures (5)

Ethics in AI: A Deep Dive

Explores the ethical implications of AI, emphasizing transparency and accountability in its applications.

22.05.2024 - Sébastien Marcel: An overview of 20 years of research in biometrics and recent work on template inversion from deep face embeddings

Affective Computing: Theories, Applications, and Predictive Models

Explores emotion theories, applications, and predictive models in affective computing, analyzing NSF funding trends, emotion impact on education and medicine, and emotion detection through physiological signals and visual data.

Related publications (17)

Simple Probability Truncation Improves Soft Red List Watermarks

Watermarking, whereby LLM outputs are steered to encode an easily identifiable digital signature, has recently gained attention as a potential solution for detecting synthetically generated text. However, watermarking schemes require tradeoffs between detectability (i.e., how easily the watermark can be identified by an algorithm) and quality of the generated text (i.e., the stylistic and semantic disruption to the normal generation of the LLM). In this work, we propose a simple extension to the Soft Red Li

2026

AI-Generated Image Detection: Challenges and Recent Advances

Recent advances in the field of AI-based content generation in combination with the easy and widespread access to such tools can enhance disinformation campaigns with respect to plausibility and scale. This poses a significant threat to online information integrity, social trust, and even democratic processes. The rapid evolution of generative models demands robust and adaptable detection mechanisms. In this chapter, we outline the progress in the field of AI-Generated Image Detection (AIGID) including rece

Springer Nature2026

2Player: A general framework for self-supervised change detection via cooperative learning

While recent progress in deep learning have improved change detection (CD) in remote sensing, achieving high performance without labeled data remains an open challenge. Current models remain strongly reliant on large-scale annotated datasets, limiting their scalability to new regions and applications. Unsupervised CD methods offer a promising alternative but often suffer from limited representational ability and vulnerability to irrelevant changes in appearance such as seasonal variations. In this work, we

2026

Related notebooks (1)

Voice Transformation Techniques Using Digital Signal Processing

A Gallery of Voice Transformers[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

In this notebook we will explore various ways to implement a system that changes the voice of a speaker. Typical applications for these techniques, strictly sorted by plausibility, include international spy missions and prank telephone calls, and devices such as the one displayed here can be easily bought on the web... or in a novelty shop. No description has been provided for t

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Official source

https://en.wikipedia.org/wiki/Audio_deepfake

About this result

Related courses (1)

EE-556: Mathematics of data: from theory to computation

Related lectures (5)

Ethics in AI: A Deep Dive

Explores the ethical implications of AI, emphasizing transparency and accountability in its applications.

22.05.2024 - Sébastien Marcel: An overview of 20 years of research in biometrics and recent work on template inversion from deep face embeddings

Affective Computing: Theories, Applications, and Predictive Models

Related publications (17)

Simple Probability Truncation Improves Soft Red List Watermarks

2026

AI-Generated Image Detection: Challenges and Recent Advances

Springer Nature2026

2Player: A general framework for self-supervised change detection via cooperative learning

2026

Related people (18)

Touradj Ebrahimi

Touradj EBRAHIMI received his M.Sc. and Ph.D., both in Electrical Engineering, from the Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland, in 1989 and 1992 respectively. In 1993, he was a research engineer at the Corporate Research Laboratories of Sony Corporation in Tokyo, where he conducted research on advanced video compression techniques for storage applications. In 1994, he served as a research consultant at AT&T Bell Laboratories working on very low bitrate video coding. He is currently Professor at EPFL heading its Multimedia Signal Processing Group. He is also the Convenor of JPEG standardization Committee. He was also adjunct Professor with the Center of Quantifiable Quality of Service at Norwegian University of Science and Technology (NTNU)from 2008 to 2012. Prof. Ebrahimi has been the recipient of various distinctions and awards, such as the IEEE and Swiss national ASE award, the SNF-PROFILE grant for advanced researchers, Four ISO-Certificates for key contributions to MPEG-4 and JPEG 2000, and the best paper award of IEEE Trans. on Consumer Electronics . He became a Fellow of the international society for optical engineering (SPIE) in 2003. Prof. Ebrahimi has initiated more than two dozen National, European and International cooperation projects with leading companies and research institutes around the world. He is a co-founder of Genista SA, a high-tech start-up company in the field of multimedia quality metrics. In 2002, he founded Emitall SA, start-up active in the area of media security and surveillance. In 2005, he founded EMITALL Surveillance SA, a start-up active in the field of privacy and protection. He is or has been associate Editor with various IEEE, SPIE, and EURASIP journals, such as IEEE Signal Processing Magazine, IEEE Trans. on Image Processing, IEEE Trans. on Multimedia, EURASIP Image Communication Journal, EURASIP Journal of Applied Signal Processing, SPIE Optical Engineering Magazine. Prof. Ebrahimi is a member of Scientific Advisory Board of various start-up and established companies in the general field of Information Technology. He has served as Scientific Expert and Evaluator for Research Funding Agencies such as those of European Commission, The Greek Ministry of Development, The Austrian National Foundation for Scientific Research, The Portuguese Science Foundation, as well as a number of Venture Capital Companies active in the field of Information Technologies and Communication Systems. His research interests include still, moving, and 3D image processing and coding, visual information security (rights protection, watermarking, authentication, data integrity, steganography), new media, and human computer interfaces (smart vision, brain computer interface). He is the author or the co-author of more than 200 research publications, and holds 14 patents. Prof. Ebrahimi is a member of IEEE, SPIE, ACM and IS&T. See the URL below for more details: http://mmspl.epfl.ch

Murat Kunt

Murat KUNT was born in Ankara, Turkey, on January 16, 1945. He received his M.S. in Physics and his Ph.D. in Electrical Engineering, both from the Swiss Federal Institute of Technology, Lausanne, Switzerland, in 1969 and 1974 respectively. From 1974 to 1976, he was a visiting scientist at the Research Laboratory of Electronics of the Massachusetts Institute of Technology where he developed compression techniques for Xray images and electronic image files. In 1976, he returned to the Swiss Federal Institute of Technology (EPFL) where, presently, he is Professor of Electrical Engineering and Director of the Signal Processing Institute, one of the largest at EPFL. He conducts teaching and research in digital signal and image processing with applications to modeling, coding, pattern recognition, scene analysis, industrial developments and biomedical engineering. His Laboratory participates in a large number of European projects under various programmes such as Esprit, Eureka, Race, HCM, Commett and Cost. He is the author or the co-author of more than two hundred research papers and fifteen books and holds seven patents. He supervised more than 60 Ph.D. students, some of them being today university professors. He has been the Editor-in-Chief of the Signal Processing Journal for 28 years and a founding member of EURASIP, the European Association for Signal Processing. He is now the Editorin-Chief of Signal, Images and Video Processing journal by Springer and serves as a chairman and/or a member of the Scientific Committees of several international conferences and on the editorial boards of the Proceedings of the IEEE, Pattern Recognition Letters and Traitement du Signal. He was the co-chairman of the first European Signal Processing Conference held in Lausanne in 1980 and the general chairman of the International Image Processing Conference (ICIP'96) held in Lausanne in 1996. He was the President of the Swiss Association for Pattern Recognition from its creation until 1997. He consults for governmental offices including the French General Assembly. He received the gold medal of EURASIP for meritorious services, the IEEE ASSP technical achievement award, the IEEE Third millennium Medal, an honorary doctorate from the Catholic University of Louvain, the technical achievement award of EURASIP and the imaging scientist of the year award of the IS&T and SPIE in 1983, 1997, 2000, 2001, 2003 and 2003 respectively. He retired in June 2008 and has been Professor Emeritus since then. Please go to: http://lts5www.epfl.ch/kunt.html for more details

Olivier Verscheure

SWISS DATA SCIENCE CENTER Housed at both EPFL and ETH Zurich, the newly created Swiss Data Science Center (SDSC) will address the fragmentation within today's data and analytics landscapes. The SDSC will be composed of a distributed multi-disciplinary team of data scientists and experts in domains including personalized health and personalized medicine, transportation, earth and environmental science, social science and digital humanities, and economics. The center aims to federate data providers, data and

Petr Motlicek

Teaching & PhD PhD Students Shashi Kumar Past EPFL PhD Students as codirector Subhadeep Dey, Weipeng He, Juan Pablo Zuluaga Gomez Courses Digital Speech and Audio Coding EE-719 The goal of this course is to introduce the engineering students state-of-the-art speech and audio coding techniques with an emphasis on the integration of knowledge about sound production and auditory perception through signal processing techniques.

Kim Lynn Uittenhove

Karl El Hajal

Sabine Süsstrunk

Prof. Dr. Sabine Süsstrunk leads the Image and Visual Representation Lab in the School of Computer and Communication Sciences (IC) at EPFL since 1999. From 2015-2020, she was also the first Director of the Digital Humanities Institute (DHI), College of Humanities (CdH). Her main research areas are in computational photography, computational imaging, color image processing and computer vision, machine learning, and computational image quality and aesthetics. Sabine has authored and co-authored over 200 publications, of which 7 have received best paper/demo awards, and holds over 10 patents. Sabine served as chair and/or committee member in many international conferences on image processing, computer vision, and image systems engineering. She is President of the Swiss Science Council SSC, Founding Member and Member of the Board (President 2014-2018) of the EPFL-WISH (Women in Science and Humanities) Foundation, Member of the Board of the SRG SSR (Swiss Radio and Television Corporation), and Member of the Board of Largo Films. She received the IS&T/SPIE 2013 Electronic Imaging Scientist of the Year Award for her contributions to color imaging, computational photography, and image quality, and the 2018 IS&T Raymond C. Bowman and the 2020 EPFL AGEPoly IC Polysphere Awards for excellence in teaching. Sabine is a Fellow of IEEE and IS&T.

Sébastien Marcel

Expertise image processing, pattern recognition, machine learning, biometrics Current work Face recognitionSpeaker recognitionMobile biometrics ( http://www.mobioproject.org )Spoofing ( http://www.tabularasa-euproject.org )Biometrics evaluation and testing ( http://www.beat-eu.org ) Sébastien Marcel is the head of the Biometrics group and senior research scientist at the Idiap Research Institute (CH), where he leads a research team and conducts research on biometrics and more particularly face recognition,

Pascal Frossard

Teaching & PhD PhD Students Yiming Qin, Alba Carballo Castro, Elisa Messori, Ke Wang, Sevda Ögüt, Tuna Alikasifoglu, William Cappelletti, Manuel Madeira, Mahdi Amiri, Ortal Yona Senouf, Vasiliki Rizou, Cem Bilaloglu, Abdellah Rahmani, Amel Abdelraheem, Jérémy Jean Philippe Baffou, Adam Hazimeh, Vincent Jung, Yike Zhao Past EPFL PhD Students Dan Jurca, Jean-Paul Wagner, Ivana Radulovic, Ivana Tosic, Effrosyni Kokiopoulou, Zafer Arican, Vijayaraghavan Thirumalai, Tamara Tosic, Eirina Bourtsoulatze, Elif Vur

Roland John Tormey

I am a sociologist and learning scientist researching and teaching on engineering education. I'm particularly focused on the roles of emotion and self-regulation in engineering teaching and learning. My profile is accessible here.

Related units (3)

L'IDIAP Laboratory

Ebrahimi Group

Signal Processing Laboratory 5

Related concepts (3)

Deepfake

Deepfakes (portmanteau of "deep learning" and "fake") are synthetic media that have been digitally manipulated to replace one person's likeness convincingly with that of another. Deepfakes are the manipulation of facial appearance through deep generative methods. While the act of creating fake content is not new, deepfakes leverage powerful techniques from machine learning and artificial intelligence to manipulate or generate visual and audio content that can more easily deceive.

15.ai

15.ai is a non-commercial freeware artificial intelligence web application that generates natural emotive high-fidelity text-to-speech voices from an assortment of fictional characters from a variety of media sources. Developed by a pseudonymous MIT researcher under the name 15, the project uses a combination of audio synthesis algorithms, speech synthesis deep neural networks, and sentiment analysis models to generate and serve emotive character voices faster than real-time, particularly those with a very small amount of trainable data.

Applications of artificial intelligence

Artificial intelligence (AI) has been used in applications to alleviate certain problems throughout industry and academia. AI, like electricity or computers, is a general purpose technology that has a multitude of applications. It has been used in fields of language translation, image recognition, credit scoring, e-commerce and other domains. Recommendation system A recommendation system predicts the "rating" or "preference" a user would give to an item.

Related notebooks (1)

Voice Transformation Techniques Using Digital Signal Processing

A Gallery of Voice Transformers[1]¶

                                      [2]Paolo Prandoni, [3]LCAV, EPFL

Related people (18)