QUESTION: 101

In which two scenarios can you use a speech synthesis solution? Each correct answer presents a complete solution.
Note: Each correct selection is worth one point.

an automated voice that reads back a credit card number entered into a telephone by using a numeric keypad
generating live captions for a news broadcast
extracting key phrases from the audio recording of a meeting
an AI character in a computer game that speaks audibly to a player

Answer(s): A,D

Explanation:

Azure Text to Speech is a Speech service feature that converts text to lifelike speech.
Incorrect Answers:
C: Extracting key phrases is not speech synthesis.

Reference:

https://azure.microsoft.com/en-in/services/cognitive-services/text-to-speech/

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QUESTION: 102

HOTSPOT (Drag and Drop is not supported)
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Note: Each correct selection is worth one point.
Hot Area:

See Explanation section for answer.

Answer(s): A

Explanation:

The translator service provides multi-language support for text translation, transliteration, language detection, and dictionaries.
Speech-to-Text, also known as automatic speech recognition (ASR), is a feature of Speech Services that provides transcription.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/Translator/translator-info-overview https://docs.microsoft.com/en-us/legal/cognitive-services/speech-service/speech-to-text/transparency-note

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QUESTION: 103

DRAG DROP (Drag and Drop is not supported)
You need to scan the news for articles about your customers and alert employees when there is a negative article. Positive articles must be added to a press book.
Which natural language processing tasks should you use to complete the process? To answer, drag the appropriate tasks to the correct locations. Each task may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
Note: Each correct selection is worth one point.
Select and Place:

See Explanation section for answer.

Answer(s): A

Explanation:

Box 1: Entity recognition the Named Entity Recognition module in Machine Learning Studio (classic), to identify the names of things, such as people, companies, or locations in a column of text.
Named entity recognition is an important area of research in machine learning and natural language processing (NLP), because it can be used to answer many real-world questions, such as:

-Which companies were mentioned in a news article?
-Does a tweet contain the name of a person? Does the tweet also provide his current location?
-Were specified products mentioned in complaints or reviews?

Box 2: Sentiment Analysis
The Text Analytics API's Sentiment Analysis feature provides two ways for detecting positive and negative sentiment. If you send a Sentiment Analysis request, the API will return sentiment labels (such as "negative", "neutral" and "positive") and confidence scores at the sentence and document-level.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/named-entity-recognition https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/how-tos/text-analytics-how-to-sentiment-analysis

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QUESTION: 104

You are building a knowledge base by using QnA Maker.
Which file format can you use to populate the knowledge base?

PPTX
XML
ZIP
PDF

Answer(s): D

Explanation:

D: Content types of documents you can add to a knowledge base:
Content types include many standard structured documents such as PDF, DOC, and TXT.
Note: The tool supports the following file formats for ingestion:
-.tsv: QnA contained in the format Question(tab)Answer.
-.txt, .docx, .pdf: QnA contained as regular FAQ content--that is, a sequence of questions and answers.
Incorrect Answers:
A: PPTX is the default presentation file format for new PowerPoint presentations.
B: It is not possible to ingest xml file directly.

Reference:

https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/concepts/data-sources-and-content

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Free AI-900 Exam Braindumps (page: 26)

QUESTION: 101

Explanation:

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QUESTION: 102

Explanation:

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QUESTION: 103

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QUESTION: 104

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