Your company plans to create a mobile app that will be used by employees to query the employee handbook. You need to ensure that the employees can query the handbook by typing or by using speech. Which core component should you use for the app?
Suggested Answer:D🗳️
Azure Cognitive Search (formerly known as "Azure Search") is a search-as-a-service cloud solution that gives developers APIs and tools for adding a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications. Your code or a tool invokes data ingestion (indexing) to create and load an index. Optionally, you can add cognitive skills to apply AI processes during indexing. Doing so can add new information and structures useful for search and other scenarios. Incorrect Answres: B: QnA Maker is a cloud-based API service that lets you create a conversational question-and-answer layer over your existing data. Use it to build a knowledge base by extracting questions and answers from your semi-structured content, including FAQs, manuals, and documents. Answer users' questions with the best answers from the QnAs in your knowledge baseג€"automatically. References: https://docs.microsoft.com/en-us/azure/search/search-what-is-azure-search
It should be A.
"Together, Language Understanding and Azure Bot Service enable developers to create conversational interfaces for various scenarios like banking, travel, and entertainment. For example, a hotel’s concierge can use a bot to enhance traditional e-mail and phone call interactions by validating a customer via Azure Active Directory and using Cognitive Services to better contextually process customer requests using text and voice. The Speech recognition service can be added to support voice commands"
https://www.luis.ai/
Agree.
Cognitive Search is used for extracting text from knowledge bases,
Text analytics recognizes up to 120 languages and can perform text to speech and vice versa.
However LUIS determines intent and entities from utterances hence is most suited for this use case
I would go with "Azure Search", as it is used for searching and can include AI processing during indexing. So I would say that it is possible to process speech/text with AI enrichment, and then perform the search...
https://docs.microsoft.com/en-us/azure/search/search-features-list
I would also go with 'Azure Search' as question talks about a Mobile App that queries an Employee Handbook, not creating a Bot for QnA or Text Analytics. Azure Cognitive search serves the purpose. https://docs.microsoft.com/en-us/azure/search/search-what-is-azure-search
recommended core component to use for the mobile app to enable employees to query the employee handbook by typing or using speech is:
A. Language Understanding (LUIS)
Assuming Handbook is like an FAQ document, QnA maker would be the answer. LUIS could still be a "core component" or a secondary component. Azure Search can mine more than one datasource, so it would be overkill but possible to achieve the solution.
I think the "expected" answer for core component is QnA maker.
I've seen several instances of microsoft saying manuals are a possible input for QnA maker. https://docs.microsoft.com/en-us/azure/cognitive-services/QnAMaker/reference-document-format-guidelines
if A is used in this case, it would be supplementary
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