You need to build a chatbot that meets the following requirements:
Supports chit-chat, knowledge base, and multilingual models
Performs sentiment analysis on user messages
Selects the best language model automatically
What should you integrate into the chatbot?
A. QnA Maker, Language Understanding, and Dispatch
B. Translator, Speech, and Dispatch
C. Language Understanding, Text Analytics, and QnA Maker
D. Text Analytics, Translator, and Dispatch
Correct Answer: C
Explanation/Reference:
Explanation:
Language Understanding: An AI service that allows users to interact with your applications, bots, and IoT devices by using natural language.
QnA Maker is a cloud-based Natural Language Processing (NLP) service that allows you to create a natural conversational layer over your data. It is used to find the most appropriate answer for any input from your custom knowledge base
(KB) of information.
Text Analytics: Mine insights in unstructured text using natural language processing (NLP)—no machine learning expertise required. Gain a deeper understanding of customer opinions with sentiment analysis. The Language Detection feature of the Azure Text Analytics REST API evaluates text input Incorrect Answers:
A, B, D: Dispatch uses sample utterances for each of your bot’s different tasks (LUIS, QnA Maker, or custom), and builds a model that can be used to properly route your user’s request to the right task, even across multiple bots.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/overview/overview
