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Practical Guide to Azure Cognitive Services

You're reading from   Practical Guide to Azure Cognitive Services Leverage the power of Azure OpenAI to optimize operations, reduce costs, and deliver cutting-edge AI solutions

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Product type Paperback
Published in May 2023
Publisher Packt
ISBN-13 9781801812917
Length 454 pages
Edition 1st Edition
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Authors (3):
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Andy Roberts Andy Roberts
Author Profile Icon Andy Roberts
Andy Roberts
Chris Seferlis Chris Seferlis
Author Profile Icon Chris Seferlis
Chris Seferlis
Christopher Nellis Christopher Nellis
Author Profile Icon Christopher Nellis
Christopher Nellis
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Toc

Table of Contents (22) Chapters Close

Preface 1. Part 1: Ocean Smart – an AI Success Story
2. Chapter 1: How Azure AI Changed Ocean Smart FREE CHAPTER 3. Chapter 2: Why Azure Cognitive Services? 4. Chapter 3: Architectural and Cost Optimization Considerations 5. Part 2: Deploying Next-Generation Knowledge Mining Solutions with Azure Cognitive Search
6. Chapter 4: Deriving Value from Knowledge Mining Solutions in Azure 7. Chapter 5: Azure Cognitive Search Overview and Implementation 8. Chapter 6: Exploring Further Azure Cognitive Services for Successful KM Solutions 9. Chapter 7: Pulling It All Together for a Complete KM Solution 10. Part 3: Other Cognitive Services That Will Help Your Company Optimize Operations
11. Chapter 8: Decluttering Paperwork with Form Recognizer 12. Chapter 9: Identifying Problems with Anomaly Detector 13. Chapter 10: Streamlining the Quality Control Process with Custom Vision 14. Chapter 11: Deploying a Content Moderator 15. Chapter 12: Using Personalizer to Cater to Your Audience 16. Chapter 13: Improving Customer Experience with Speech to Text 17. Chapter 14: Using Language Services in Chat Bots and Beyond 18. Chapter 15: Surveying Our Progress 19. Chapter 16: Appendix – Azure OpenAI Overview 20. Index 21. Other Books You May Enjoy

Building a complete batch solution

In this chapter, we use the Speech service to translate audio files that are sent into Azure Blob Storage. When the file is created, we can then choose to perform other downstream activities – for example, extracting a sentiment from the document and tracking the results. The following diagram shows the process that we follow to monitor the storage account, begin the async request to start the transcription, and once the transcription is complete, write the results file to Azure Blob Storage:

Figure 13.8 – Process outline for creating a transcript from an audio file

Figure 13.8 – Process outline for creating a transcript from an audio file

To support this process, we create the following:

  • Azure Cognitive Speech service to perform the transcription activity.
  • Azure Storage account:
    • Blob container to store audio files.
    • Blob container to store transcription results.
    • Storage table to track transcription job progress.
  • Azure Functions App:
    • One function to monitor the audio...
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