AI models

Face Detection & Recognition

Build reliable facial recognition systems to access to personal devices, information using biometrics, vision guided machine learning and deep learning.

Applications
Emotion Recognition

Detect human emotions using machine learning and deep learning models to evaluate non-verbal responses to products, services or goods. Using face detection algorithms, emotions can be analysed by examining the sentiments on a human face by utilizing sophisticated image dispensation.

Automated lip reading

Various algorithms and computation techniques are used to recognize speech into text and improve its accuracy of transcription using statistical modeling systems with complex probability and mathematical functions to determine the most likely outcome. Customised speech recognition models can be used along with acoustic models, a pronunciation dictionary, and language models to transcribe domain-specific terms and rare words by providing hints and improving transcription accuracy of specific words which powers virtual assistants, facilitating automated closed captioning, and enabling digital dictation platforms.

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