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PresentID Speaker verification API 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 pass over benchmarks such as the Andrew Zisserman Group at Oxford University. In contrast with other methods they 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. Another detail of our model is robust to the environment and virtual noises.
How to try demo?
Read the passage shown on the screen.
Drop the file in the box
See the result
For developer, Json result is available too
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.
Ability & Potentials 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
I like to travel to paris and visit Eiffel tower.
Upload Second Voice
I want to try your speaker verification service free. Please show me the result.
Try Speaker Verification in
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PresentID Speaker verification API checks whether two voices belong to the same person or not.