How do you make a deepfake? (2024)

Temps de lecture: 5 minutes

Deepfake, a combination of the terms “deep learning” and “fake”, refers to an image synthesis technique based on artificial intelligence (AI) capable of creating or modifying videos and images with a high degree of realism. First appearing in autumn 2017 on Reddit, deepfake quickly captured the attention of the general public and the media, causing as much fascination as concern.

This technology is based on the use of convolutional neural networks, a specific form of AI that mimics the workings of the human brain to learn to recognise patterns in large quantities of data. In particular, deepfakes are capable of superimposing the face of one person on that of another in a video, modifying facial expressions or even synthesising speech to make someone say words they have never spoken.

The practical applications of deepfake are varied, ranging from entertainment and advertising to education and historical reconstruction. However, the ethical implications and potential abuses of this technology, such as disinformation, political manipulation and invasions of privacy, raise serious concerns.

Preparation

Before embarking on the creation of a deepfake, several preparatory steps are essential to guarantee the success of the project. Careful selection of the tools and software best suited to the designer’s specific needs is essential. Selection criteria include ease of use, quality of results and, above all, the availability of free or low-cost versions for beginners.

Collecting and selecting the source data is also a critical stage. To create a convincing deepfake, you need high-quality video or images. The faces must be clear, well-lit and captured from different angles to enable the AI to learn the characteristics of the target face efficiently. This phase often includes meticulous research to find material that respects copyright and the consent of the people depicted.

How to make a free Deepfake?

Access to deepfake creation tools does not necessarily require a financial investment. A number of platforms offer free versions or trials that allow you to familiarise yourself with deepfake creation at no initial cost.

• Free tools and platforms: Platforms such as DeepFaceLab offer open-source versions that, while requiring some learning, allow you to create quality visual deepfakes. FakeApp is another option that has popularised the creation of deepfakes among the general public thanks to its relatively accessible interface.
• Tutorials and Resources: Many online tutorials explain how to use these tools, guiding beginners through the steps involved in creating a deepfake. Online forums and communities, such as Reddit, also offer a place to exchange tips and tricks.
• Tips for maximising free resources: Using open-source software and following the guides available online can greatly reduce the barrier to entry. It’s also a good idea to experiment with different tools to find the one that best suits your specific needs.

Creating Vocal Deepfakes

The creation of voice deepfakes opens up a fascinating field of experimentation. Thanks to advances in AI, it is now possible to synthesise a person’s voice with astounding accuracy, offering applications ranging from personalising voice assistants to creating immersive audio content for video games and audio books.

1. iMyFone VoxBox is an easy-to-use tool that generates a deepfake voice from simple text. Users can choose from a vast library of voices or even clone their own voice to create personalised audio content.
2. FakeYou is a free online platform for creating realistic synthetic voices. It offers the possibility of generating audios in a multitude of voices, including those of famous people, making it a popular tool for digital content creators wishing to add an audio dimension to their projects.
3. Uberduck.AI relies on Google’s Tacotron 2 technology to provide a rich user experience, enabling the creation of deepfake audio tracks with a wide range of voices. Its intuitive interface and the quality of its results make it the solution of choice for professionals and amateurs alike.

Création de Deepfakes Visuels

The creation of visual deepfakes, which involves manipulating videos or images to alter appearances, has become remarkably accessible thanks to advances in artificial intelligence. However, mastering the art of producing convincing deepfakes requires not only the right tools but also an in-depth understanding of the principles of machine learning.

1. Creation methodologies: The process begins by training an AI model on a dataset consisting of numerous images or videos of the person to be imitated. This training enables the model to learn to reproduce movements and facial expressions realistically. Software such as DeepFaceLab or Faceswap is frequently used for this process, giving users the opportunity to customise their creations.
2. Tools and applications :
   • DEEPSWAP AI stands out for its ease of use, enabling users to create direct deepfakes simply by uploading source images or videos. It offers an intuitive interface that democratises access to this technology.
   • Heygen offers a unique approach to animating static photos, turning simple images into talking videos with dynamic facial expressions.

Ethical and legal considerations

The creation and dissemination of deepfakes raises important ethical and legal issues, particularly in terms of consent, privacy and misinformation.

• Consent and Image Rights: Respect for people’s image rights is essential. It is essential to obtain the explicit consent of individuals whose faces or voices are used in the creation of deepfakes.
• Risks of misinformation and social impact: deepfakes can be used to create false information or manipulate perceptions, with potentially serious consequences for society. Awareness-raising and education on the detection of deepfakes are essential to counter these risks.
• Legal Framework and Regulation: Laws concerning deepfakes vary from country to country, but generally tend to protect against the misuse of this technology. Deepfakes creators should be aware of the legal implications of their actions and comply with applicable laws.

Advice and best practice

To create quality deepfakes while remaining ethical, here are a few tips and best practices to consider:

• Optimising the quality of deepfakes: The key to a successful deepfake lies in the quality of the source data. Use high-resolution videos and images and make sure that facial expressions and movements are clearly visible. Experiment with different settings in your software to get the best results.
• Responsible use of deepfakes: Always obtain the consent of the people involved before creating or sharing a deepfake about them. Think carefully about the impact of your creation on the people represented and on the public.
• Detecting deepfakes: Educate yourself and your audience about the tools and techniques for detecting deepfakes. This can help prevent the spread of false information and raise awareness of the ethical implications of deepfakes.

Innovative applications of Deepfakes

Deepfakes have the potential to innovate in a variety of areas, beyond their controversial use to create misleading content:

• Cinema and entertainment: Deepfakes can be used to enhance special effects, making it possible to rejuvenate actors or recreate performances by deceased actors in a respectful and realistic way.
• Education and training: Deepfakes can make learning more interactive and engaging, for example by recreating historical speeches or simulating dialogues with historical figures.
• Simulation and modelling: In the fields of research and engineering, deepfakes can help visualise environmental changes, simulate security scenarios or train AI to recognise facial expressions in a variety of contexts.

Conclusion

Deepfakes represent a remarkable technological advance, offering creative and innovative possibilities in many sectors. However, their potential to cause harm underlines the importance of responsible and ethical use. As the technology continues to evolve, it is crucial to develop effective regulatory frameworks and detection tools to prevent abuse. At the same time, educating the public about deepfakes and their implications is essential to navigating this new era of content creation. Ultimately, the future of deepfakes will depend on how we, as a society, choose to embrace them, focusing on positive innovation while minimising the potential risks.

Sommaire