Use Cases Of Natural Language Understanding Training Ppt

Slide 1

This slide lists the use cases for natural language understanding, such as automatic ticket routing, automated reasoning, machine translation and question answering.

Slide 2

This slide states that customer service automation is an excellent corporate example of NLU. Machines can interpret the content of customer support tickets and route them to the appropriate departments without requiring people to open every ticket. This saves customer service employees hundreds of hours and allows them to prioritize urgent requests.

Slide 3

This slide describes that a subject of cognitive science known as automated reasoning is used to mechanically prove mathematical theorems or form logical conclusions regarding a medical diagnosis. It provides machines with a type of thinking or logic, allowing them to infer new facts through deduction.

Instructor Notes: 

Computer algorithms may create conclusions based on previously obtained and processed data. In medicine, for example, using IF-THEN deduction rules, robots may deduce a diagnosis based on past diagnoses.

Slide 4

This slide states that one of the most problematic tasks in NLP and NLU is accurately translating voice or text from one language to another. Machine translation technologies allow you to enter words or upload whole documents and obtain translations in dozens of languages.

Instructor Notes:

Google Translate incorporates optical character recognition (OCR) software, enabling machines to extract text from photos, interpret it, and translate it.

Slide 5

This slide describes that answering questions is a branch of NLP and voice recognition that use NLU to assist computers in understanding natural language inquiries.

Instructor Notes: 

Unless you designate a specific city, virtual assistants will tell you the weather for your present location by default. The purpose of question answering is to respond in the user's native language rather than a list of written replies.