We provide a multi-modal digital identity verification through face and voice biometrics. One layer of security that can add more accuracy on detecting fraud is the voice(speaker) verification.
PresentID Speaker verification API/SDK checks whether two voices belong to the same person or not. This capability is potentially useful in call centers.
We have proposed a deep learning-based method for speaker verification. Our team worked on this project for more than 1 year and the accuracy has passed over benchmarks such as the accuracy of the paper by Andrew Zisserman Group at Oxford University. In contrast with other methods that are text-dependent, our model is text and language-independent. On the other hand, the processing speed of our model is less than 1 sec and the model verifies a person by just two voices with a length of 4 secs. We have trained the model on tracks with English, French, Spanish, German, Persian, and Arabic languages. Our model is robust to the environment and virtual noises.
How to try the demo?
1. Open this page on your mobile phone
2. Click on "Uploqd first voice" and choose your recorder
3. Read the text on the screen or say anything you want at least 4 seconds
4. Click on "Uploqd second voice" and choose your recorder
5. Repeat the third step
6- Check out the result
Rules & Restrictions Send data via Base64 or a voice URL or voice file. The voice must be between three seconds and one minute. The voices must not exceed 5 MB. Supported file types: WAV, MP3, M4A, FLAC, AAC, OGG.
Features Accuracy over 90%. Less than 1 second processing time. No need for GPU. Language & text-independent. Easy integration with your app. Support IOS, Android, Windows, and Mac devices. Easy integration with your app.
Use Cases Call center
Upload First Voice
Upload Second Voice
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PresentID Speaker verification API checks whether two voices belong to the same person or not.