Introducing Resemble Detect: The Antivirus for AI


Antivirus for AI

Combat AI-based fraud effectively with Resemble Detect, our advanced neural model designed for real-time deepfake audio detection.

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Over 200,135 AI voices generate more than 2,000,000 minutes of audio per month on Resemble!

Detect Deepfake Voices in the Wild.

From music to podcasts, Detect recognizes deepfake audio across all forms of media and against all modern generative AI speech synthesis solutions.

Resemble Detect works to identify Drake and Weeknd AI Singing Deepfake

Heart on my Sleeve, Drake ft. The Weeknd

Resemble Detect works to identify Joe Biden deepfake.

US President Joe Biden Transphobic Remarks

Resemble Detect works to identify Joe Rogan deepfake.

Podcast Host, Joe Rogan TikTok Endorsements

AI Watermarker

🔒 Protect your IP.

Your data should belong to you. We build our AI Watermarker to protect your data from being used by unauthorized AI models. When you protect your IP with our Watermarker, you can determine whether an AI model used your data during training.

For Developers

Technologist on Apple iOS 16.4 API Ready.

Empower your applications to recognize deepfake audio across a myriad of media types, from music to podcasts, combating AI fraud by leveraging cutting-edge neural models.

Resemble AI Detect API

How does Deepfake Voice Detection work?

Detect uses a state-of-the-art deep neural network that is trained to identify spoofs from real audio. It works frame-by-frame, so any amount of inserted audio can be recognized.


Accuracy for Deepfake Detection

Integrating Detect in your Stack

Detect is a market-ready solution for those needing robust authentication, boasting strong performance and low complexity for easy integration. Our APIs make it simple for Developers to integrate Detect into their application.

More FAQs

What is Resemble Detect and how does it help in identifying deepfake audio?

Resemble Detect is a state-of-the-art neural model designed to expose deepfake audio in real-time. It works across all types of media, and against all modern state-of-the-art speech synthesis solutions. By analyzing audio frame-by-frame, it can accurately identify and flag any artificially generated or modified audio content.

Can Resemble Detect help protect my Intellectual Property?

Yes, Resemble AI offers an AI Watermarker to protect your data from being used by unauthorized AI models. By watermarking your data, you can verify if an AI model used your data during its training phase.

How does Resemble AI's watermarker persist through model training?

Resemble AI’s watermarker is designed to endure throughout the model training process. This means that the watermark, or the unique identifier, remains intact even after the data has undergone various transformations during training.

How does Resemble AI's technology contribute to content creation?

Resemble AI’s generative AI Voices are production-ready and offer a revolutionary way to create content. Whether it’s creating unique real-time conversational agents, translating a voice into multiple languages, or generating thousands of dynamic personalized messages, Resemble AI is altering the content creation landscape. It adds a new level of authenticity and immersion to your content, enhancing audience engagement and overall quality.

How is Resemble Detect trained to identify deepfake audio?

Resemble Detect uses a sophisticated deep neural network that is trained to distinguish real audio from spoofed versions. It analyzes audio frame-by-frame, ensuring any amount of inserted or altered audio can be accurately detected.

How does Resemble AI utilize psychoacoustics in their technology?

Psychoacoustics, the study of human sound perception, plays a significant role in Resemble AI’s technology. By understanding that human sensitivity varies with different frequencies, the technology can embed more information into frequencies we are less sensitive to. Additionally, it utilizes a phenomenon called “auditory masking” where quieter sounds in frequency and time to a louder sound are not perceived, thereby allowing data to be encoded beneath such ‘masking’ sounds.

How does Resemble AI ensure data recovery rate in the presence of various "attacks"?

Resemble AI applies various regularization methods to the model training procedure to resist different types of attacks. Even after applying “attacks” like adding audible noise, time-stretching, time-shifting, re-encoding, and more, nearly 100% data recovery rate can be achieved.

Can I detect if my data was used in training other models with the help of Resemble AI's watermarker?

Absolutely. Because Resemble AI’s watermarker persists through model training, it can be used to identify if your data was used in training other AI models. This feature adds an extra layer of security and allows for better control and protection of your data.