The Exam AI-900 Microsoft Azure AI Fundamentals dives deep into several AI products and services offered by Microsoft Azure. One such service is the Azure Language Service, which provides capabilities that boost natural processing of language in your applications. In this article, we’ll experiment with the capabilities of Azure Language Service, discussing what they mean for your business, and how to best utilize them.
Here are the key features;
1. Text Analytics
Text analytics is a feature that processes and analyzes unstructured text for tasks such as sentiment analysis, key phrase extraction, named entity recognition (NER), and language detection. The features include:
- Sentiment Analysis:This helps detect positive, neutral, or negative sentiments from raw text. For instance, it could be used to monitor customer feedback and determine their satisfaction level from textual comments.
- Key Phrase Extraction: It identifies the key talking points in text. You could use this to identify common issues in customer comments.
- Named Entity Recognition (NER): It identifies and categorizes entities in your text as people, places, organizations, date/time, quantities, percentages, currencies, and more. NER can be useful for extracting specific information from large volumes of text.
- Language Detection: This is used to detect up to 120 languages, even in a single document. It’s an essential tool when dealing with global, multilingual users.
2. Language Understanding
The Language Understanding service, also known as LUIS, instructs your application to understand user commands contextually. For instance, a user may say “turn off the lights” or “dim the lamps,” where both phrases imply the same action. LUIS helps the application understand this context and execute the appropriate action.
3. Translator Text
The Translator Text service allows your application to offer real-time, automatic text translation in over 60 languages. This ensures inclusivity for users around the globe and ensures seamless multilingual communication.
4. Speech Service
The Speech Service offers various functionalities, including text-to-speech, speech-to-text, and speech translation. This makes the application more accessible and interactive for users who speak, or want content read out in, different languages.
5. QnA Maker
The QnA Maker service can extract questions and answers from any given content. It essentially helps you build a question-answering bot from your existing content.
6. Custom Language Understanding
Lastly, Custom Language Understanding allows businesses to tailor Azure’s language understanding to their specific needs. For example, a layperson’s language might differ considerably from technical jargon used in software development. Custom Language lets you train your own language model to understand this unique usage.
Conclusion
In conclusion, the Azure Language Service equips your applications with the capability to understand and simulate human language, making them more engaging and useful to a broad range of users. Besides, it offers a customizable language model to uniquely address particular business needs. This makes it an essential tool for developers looking to enhance user experience in their Azure-based applications.
Practice Test
True or False: Microsoft Azure’s Language service cannot translate text.
- False
Answer: False
Explanation: Microsoft Azure’s Language service provides text translation capabilities supporting multiple languages.
Which of the following can Azure’s Language service do?
- A) Sentiment Analysis
- B) Text Translation
- C) Named Entity Recognition
- D) None of the above
Answer: a) Sentiment Analysis, b) Text Translation, c) Named Entity Recognition
Explanation: Azure’s Language service has capabilities for sentiment analysis, text translation and named entity recognition, among others.
True or False: Azure Language service doesn’t have a feature like Language Understanding (LUIS).
- False
Answer: False
Explanation: The Azure Language service includes Language Understanding (LUIS), which aids in extracting meaningful information from natural language input.
Which Azure service provides support for the creation of custom machine learning models without requiring coding knowledge?
- A) Azure Machine Learning
- B) Azure Text Analytics
- C) Azure Document Translation
- D) Azure Immersive Reader
Answer: a) Azure Machine Learning
Explanation: Azure Machine Learning offers a studio interface that allows to create custom ML models without writing any code.
True or False: Sentiment Analysis performed by Azure Language Service can score the sentiment of a document?
- True
Answer: True
Explanation: Sentiment Analysis is a part of Azure Language service that scores the overall sentiment of a document from 0 (negative) to 1 (positive).
Azure Speech service is a part of which group?
- A) Cognitive Services
- B) Language Services
- C) Translator Text
- D) Text Analytics
Answer: a) Cognitive Services
Explanation: Azure Speech service, which includes features like speech to text, text to speech etc., is part of the Azure cognitive services.
What is `entities` in Named Entity Recognition (NER) provided by Azure Language Service?
- A) Sentences
- B) Words
- C) Hotspots
- D) Named entities
Answer: d) Named entities
Explanation: In NER, ‘entities’ refer to named entities like person names, organizations, locations, etc.
Which service from Azure allows real-time multi-language translation for applications, websites, and tools?
- A) Azure Text Analytics
- B) Azure Speech service
- C) Azure Translator
- D) Azure QnA Maker
Answer: c) Azure Translator
Explanation: Azure Translator provides real-time multi-language translation capabilities for various platforms.
Azure’s Language detection API can detect more than 60 languages. True/False?
- True
Answer: True
Explanation: Azure’s Language Detection API can indeed detect more than 60 languages, making it versatile and effective.
Which of the following entities can be recognized by Named Entity Recognition in Azure’s Language Service?
- A) People
- B) Quantity
- C) Currency
- D) Impression
Answer: a) People, b) Quantity, c) Currency
Explanation: Named Entity Recognition can identify various types of entities like people, quantity, and currency. ‘Impression’ is not a formally recognized entity type.
Interview Questions
What is Language Understanding Intelligent Service (LUIS) and how is it utilized in Microsoft Azure AI?
LUIS is a service offered by Microsoft Azure AI that lets applications understand and interpret natural language inputs. LUIS uses machine learning to enable applications to understand specific tasks, such as determining user intentions from their queries, and to extract relevant pieces of information from those commands.
What is Azure Text Analytics API?
Azure Text Analytics API is a cloud-based service that provides advanced natural language processing over raw text. It includes four main functions: sentiment analysis, key phrase extraction, named entity recognition, and language detection.
What are the capabilities of the Text Analytics Service in Microsoft Azure AI?
The Text Analytics Service can detect the language of a text document, extract key phrases, analyze sentiment, and identify named entities such as people, places, organizations, and date time.
What is the output of the Text Analytics API’s sentiment analysis function?
The sentiment analysis function of the Text Analytics API returns a sentiment score between 0 and 1 for each document, where 1 is the most positive and 0 is the most negative.
How does the entity recognition feature of Azure Text Analytics API work?
The entity recognition feature of Azure Text Analytics API identifies and categorizes entities in your text as people, places, organizations, date/time, quantities, percentages, currencies, and more.
Does Microsoft Azure AI offer translation services?
Yes. Azure AI offers the Translator Text API for real-time text translation and localization. It supports over 60 languages for translation.
Define the functionality of Azure’s Translator Speech service.
Azure’s Translator Speech service is designed to transcribe spoken words into written text and vice versa. This service also supports translation between a variety of languages in real-time.
What are the usage scenarios of Language Understanding (LUIS)?
You can use LUIS in various scenarios such as creating chatbots for customer service, virtual assistants for voice-activated software, translation services, and more.
What is the name of the Microsoft Azure AI service that performs personal identification using different voices?
The name of the Microsoft Azure AI service that performs this task is the Speaker Recognition API.
Can Azure AI provide language services for multilingual documents?
Yes. Azure AI’s Text Analytics API is capable of detecting multiple languages in a single document and applying the necessary actions for each detected language.
What is the role of the Microsoft Immersive Reader in the Azure AI language service?
The Microsoft Immersive Reader is a service that assists users in improving their reading and comprehension skills. It provides several capabilities such as a full-screen reading experience, read aloud text, and translation into multiple languages.
Can LUIS understand different domains like weather, music, and devices?
Yes. By adding prebuilt domains to your LUIS application, LUIS can understand language related to those specific domains such as weather, music, and devices.
Is it possible to customize the language models in LUIS according to business-specific needs?
Yes. LUIS allows customizing the language model according to the specific needs of the business, improving the application’s understanding of the specific commands related to the organization.
Can Text Analytics API in Azure recognize and categorize personal information in a text?
Yes, Text Analytics API offers a feature called Personally Identifiable Information (PII) Entities Recognition which recognizes and categorizes PII in a text.
Can Azure Text Analytics API detect the emotional sentiment from customer reviews?
Yes, one of the features of Azure Text Analytics API is sentiment analysis which determines the positive, negative, mixed or neutral sentiments from text such as customer reviews.
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