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NEW QUESTION: 1
次の充電ポートとデータポートのうち、無向コネクタがあるのはどれですか？
A. USB-A
B. マイクロUSB
C. USB-C
D. ミニUSB
Answer: C

NEW QUESTION: 2
Which of the following statements is an accurate value statement of the Agile Manifesto?
A. Customer collaboration over contract negotiation
B. Working software over complete specifications
C. People and places over processes and guidelines
D. Managing change over managing a plan
Answer: A

NEW QUESTION: 3
You plan to create a bot that will support five languages. The bot will be used by users located in three different countries. The bot will answer common customer questions. The bot will use Language Understanding (LUIS) to identify which skill to use and to detect the language of the customer.
You need to identify the minimum number of Azure resources that must be created for the planned bot.
How many QnA Maker, LUIS and Language Detection instances should you create? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

QnA Maker: 5
If the user plans to support multiple languages, they need to have a new QnA Maker resource for each language.
LUIS: 5
If you need a multi-language LUIS client application such as a chatbot, you have a few options. If LUIS supports all the languages, you develop a LUIS app for each language. Each LUIS app has a unique app ID, and endpoint log. If you need to provide language understanding for a language LUIS does not support, you can use Microsoft Translator API to translate the utterance into a supported language, submit the utterance to the LUIS endpoint, and receive the resulting scores.
Language detection: 1
The Language Detection feature of the Azure Text Analytics REST API evaluates text input for each document and returns language identifiers with a score that indicates the strength of the analysis.
This capability is useful for content stores that collect arbitrary text, where language is unknown. You can parse the results of this analysis to determine which language is used in the input document. The response also returns a score that reflects the confidence of the model. The score value is between 0 and 1.
The Language Detection feature can detect a wide range of languages, variants, dialects, and some regional or cultural languages. The exact list of languages for this feature isn't published.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/overview/language-support
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/luis-language-support
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-language