AI-900 Question 189
Select 3A company wants to build a chatbot that can understand customer queries and provide relevant responses. They are considering using Azure Cognitive Services for this task. Which features of Azure's Natural Language Processing (NLP) services can help in achieving this goal?
- A
Language Understanding (LUIS) for interpreting the intent and entities in user queries
- B
Text Analytics for detecting sentiment in user messages
- C
Speech to Text for converting spoken input into text
- D
QnA Maker for creating a knowledge base from frequently asked questions
- E
Azure Monitor for tracking the performance of the chatbot
Show answer and explanation
Correct answers: A, B, D
Explanation
For a chatbot that processes customer queries, Azure's NLP features like Language Understanding (LUIS) for intent and entity recognition, Text Analytics for sentiment analysis, and QnA Maker for building a knowledge base are essential. These services enable the chatbot to understand user input, analyze sentiment for better interaction, and provide accurate responses using pre-defined knowledge bases.
- A. Correct.
Language Understanding (LUIS) is a core NLP feature on Azure that helps in identifying intents and extracting entities from user queries, which is critical for chatbot functionality.
- B. Correct.
Text Analytics can analyze user messages to detect sentiment, which can be used to provide more empathetic or context-aware responses in the chatbot.
- C. Incorrect.
Speech to Text is not directly related to NLP in this case as the scenario focuses on understanding text-based queries, not converting spoken input.
- D. Correct.
QnA Maker is a useful Azure service for creating a knowledge base from FAQs, which can be integrated into the chatbot to provide relevant responses to common queries.
- E. Incorrect.
Azure Monitor is a service for monitoring Azure resources but is not directly related to the NLP capabilities required to understand and respond to user queries.