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In this lesson, we explore various Azure services for Natural Language Processing (NLP), focusing on how machines can interpret, understand, and respond to human language. The lesson is structured to guide you through text analysis, question answering, chatbot development, conversational language understanding, and speech recognition/synthesis.

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Text Analysis

We start by discussing how Azure supports text analysis to extract key phrases, entities, and other critical information. This capability is essential for summarizing large volumes of text and identifying core concepts. In the upcoming lab session, you will work hands-on with Azure Language Studio to apply these text analysis techniques on real-world examples.
The image is a module introduction slide listing four topics: Text Analysis, Text Analysis Using Language Studio (Lab), Question Answering, and Azure Bot Service. It features a gradient blue background on the left with numbered labels for each topic.

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Question Answering and Azure Bot Service

Next, we examine Azure’s Question Answering capabilities. Here, you will learn to configure systems that respond to queries based on a dataset or knowledge base. Imagine building a bot that efficiently answers customer inquiries using historical records. Following the question answering discussion, we introduce Azure Bot Service. This service empowers you to create conversational AI chatbots that naturally understand and address user queries.
A dedicated lab session will guide you through implementing a QnA Model using Azure Language Studio. This interactive segment will help you consolidate your understanding of text analysis and question answering.

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Conversational Language Understanding and Speech Recognition

In the subsequent section, we delve into conversational language understanding. Learn how NLP models process conversational contexts and manage intricate language queries effectively. Finally, we cover speech recognition and synthesis. This topic addresses converting spoken words into text and vice versa, unlocking potential for developing voice-activated applications and digital assistants.
The image is a module introduction slide listing topics such as Q&A Model Using Language Studio, Conversational Language and Understanding, and Speech Recognition and Synthesis. It features a gradient background with numbered labels for each topic.
We conclude the module with an in-depth exploration of speech recognition and synthesis. Now, let’s get started with text analysis and uncover the power of Azure’s NLP capabilities.

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