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Interactive Emotions Analyzer

To collaborate and be a valued partner in frontier technology
for organizations in their digital evolutionary journey



Identified 62% accuracy in elderly people emotions.

Paris

Goal

To identify the state of emotion by appearance and to talk to elderly people based on their response.

Insights and Action

Virtual avatars being used in customer engagement platforms engages, educate and empower users. Humanized avatar does voice interaction with the elderly people. The system is a combination of both text and computer vision understanding to respond to the patients in the chat.

Entire architecture of the machine learning systems include the secured layers both frontend and backend and predictive Al on top of it.

This system has mobile apps, web dashboard with compliances such as HIPAA, SOX inline with the healthcare industry.

Results

62%

Of the elderly people emotions/appearances were accurately identified with voice interaction providing them a little relief.







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