Deepfake Detection
Robust deepfake detection combines efficient architecture with unparalleled accuracy across diverse languages and generation methods
Neural Watermark
Sophisticated deep neural network watermarker developed by Resemble AI that embeds imperceptible data into generated speech content
Identities
Leverages cutting-edge AI to create unique voice profiles, offering unparalleled accuracy in speaker recognition across various applications.
Audio Intelligence
Empower decision-making with AI-Driven, explainable Audio Intelligence: detect deception, language, dialect, emotion, topic, and fact checking
Explore DETECT-2B: Our 2 Billion Parameter Deepfake Detection Model
DETECT-2B’s groundbreaking approach to deepfake detection combines efficient architecture with unparalleled accuracy across diverse languages and generation methods
Dashboard for Transparency
A complete dashboard to monitor detect activity and generate predictions using simple drag and drop.
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.
Heart on my Sleeve, Drake ft. The Weeknd
US President Joe Biden Transphobic Remarks
Podcast Host, Joe Rogan TikTok Endorsements
Complete Control for Complete Security.
Detect exposes knobs and control operations to ensure that every application and requirement is met. Have control over the granularity of the analysis, sensitivity towards false-positives, and vocal isolation for to remove the noise.
Step 1
Configure Your Settings: Customize detection settings to match your specific security needs.
Step 2
Upload Your Audio: Detect’s cutting edge technology accepts WAV, MP3, and similar file formats.
Step 3
Analyze & Verify: Start monitoring your audio content. Resemble Detect will analyze and provide real-time alerts on suspicious content.
For Developers
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.
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.
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.