Sense

Reaching true intelligence beyond data processing and analytics.

Ardi Sense

Senses are how the human brain perceives and relates to the world. When senses are stimulated, the human brain receives a certain signal which triggers different emotions and actions.

Ardi Sense includes Natural Language Processes (NLP) and Deep Video Understanding, which helps machines to identify and understand different inputs through language or image, allowing machines to understand sentiment within context and therefore reaching true intelligence beyond data processing and analytics.


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Natural Language Processing (NLP)

With the help of Ardi Sense NLP Sentiments, users can analyze sentiments expressed through natural language within context. It takes semantics into consideration by using logic and linguistics to identify and establish the meaning of a text based on its context, allowing machines to understand the different emotions contextually.

This technology can be applied to many different industries. For example, it can help with online customer services, record understading, compliances, etc.

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Deep Video Understanding

Ardi Sense Deep Video Understanding automatically deduces relationships between entities via long-term multi-modal inputs and extract knowledge to address varied query-types.

It integrates scene recognition, facial recognition, speech recognition, language understanding, speaker identification, entity interaction, conversation recognition, emotion recognition, knowledge graph formation and knowledge graph query seamlessly.


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Use Case

Fabien is a psychologist working in the internet medical industry. His company is developing an online chatbot that can accompany depression patients and monitor their mental health.

With the help of Ardi Sense NLP Sentiments, the chatbot analyzes sentiments expressed through natural language within context. It takes semantics into consideration by using logic and linguistics to identify and establish the meaning of a text based on its context, allowing machines to understand the different emotions contextually. When the patient’s emotional score falls below a certain threshold, the application will arrange a designated doctor to treat the patient.

This technology can help the medical industry to manage resources more reasonably and reduce labor costs.

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