⚡️ Introducing DETECT-2B, the most advanced deepfake detection model

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Twilio with Custom AI Voice

Deepfake Detection for Twilio

Integrate Resemble Detect with Twilio Voice to build scalable and secure voice experience with the Voice API that’s connecting millions around the world.

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200ms to Response

Detect is able to handle large volumes of data and requests without significant delays.

Seamless Integration

Seamlessly connect Twilio to Resemble Detect in minutes to start analyzing all voice activity on your Twilio Voice channels.

Remove Noise

We isolate the voice when processing to improve accuracy and stability of our prediction.

Process the Voice stream in realtime.

Integrating Resemble Detect with Twilio Voice transforms real-time voice interactions, offering immediate insights and actions based on voice stream analysis. This powerful combination enables businesses to leverage voice biometrics for instant authentication, sentiment analysis, and personalized communication, ensuring a seamless and secure user experience.

Realtime Dashboard for results

Read Deepfake Incident Reports

Arcads AI Deepfake Video

Arcads AI Deepfake Video

On March 25, 2024, a Twitter user named Beck (@beckylitv) posted a 46-second video that was...

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.