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AI-900: How to Use Azure Services for Chatbot Development

Learn how to use Azure services to develop a chatbot solution that can understand the user’s intent and provide relevant answers. Find out which service is best for natural language processing and why.

Question

You are developing a chatbot solution in Azure. Which service should you use to determine a user’s intent?

A. Translator Text
B. QnA Maker
C. Speech
D. Language Understanding (LUIS)

Answer

D. Language Understanding (LUIS)

Explanation

Language Understanding (LUIS) is a cloud-based API service that applies custom machine-learning intelligence to a user’s conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.

Design your LUIS model with categories of user intentions called intents. Each intent needs examples of user utterances. Each utterance can provide data that needs to be extracted with machine-learning entities.

The correct answer is D. Language Understanding (LUIS). Language Understanding (LUIS) is a cloud-based service that enables you to build natural language understanding into your applications, bots, and IoT devices. With LUIS, you can design and deploy custom models that can recognize and extract the meaning from user inputs, such as text or speech.

To determine a user’s intent, you need to create a LUIS app that defines the possible intents and entities that are relevant to your chatbot solution. An intent is a goal or action that the user wants to achieve, such as booking a flight or ordering a pizza. An entity is a detail or parameter that clarifies the intent, such as the destination, date, or size of the pizza.

For example, if the user input is “I want to fly to Paris on Friday”, the intent could be “BookFlight” and the entities could be “Paris” and “Friday”. LUIS uses machine learning to analyze the user input and predict the most likely intent and entities. You can then use the intent and entities to provide an appropriate response or action for your chatbot solution.

Translator Text, QnA Maker, and Speech are not the best services to use to determine a user’s intent. Translator Text is a service that can translate text from one language to another. QnA Maker is a service that can create a knowledge base of questions and answers from existing sources, such as websites, documents, or manuals. Speech is a service that can convert speech to text and text to speech, as well as perform speech translation and speaker recognition. These services can be useful for enhancing the functionality of your chatbot solution, but they do not directly help you to understand the user’s intent. Therefore, Language Understanding (LUIS) is the most suitable service for this purpose.

Reference

Microsoft Learn > Azure > Cognitive Services > Language Understanding (LUIS) > What is Language Understanding (LUIS)?

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook

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