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Learn OpenAI Whisper

Learn OpenAI Whisper

By : Josué R. Batista
4.9 (13)
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Learn OpenAI Whisper

Learn OpenAI Whisper

4.9 (13)
By: Josué R. Batista

Overview of this book

As the field of generative AI evolves, so does the demand for intelligent systems that can understand human speech. Navigating the complexities of automatic speech recognition (ASR) technology is a significant challenge for many professionals. This book offers a comprehensive solution that guides you through OpenAI's advanced ASR system. You’ll begin your journey with Whisper's foundational concepts, gradually progressing to its sophisticated functionalities. Next, you’ll explore the transformer model, understand its multilingual capabilities, and grasp training techniques using weak supervision. The book helps you customize Whisper for different contexts and optimize its performance for specific needs. You’ll also focus on the vast potential of Whisper in real-world scenarios, including its transcription services, voice-based search, and the ability to enhance customer engagement. Advanced chapters delve into voice synthesis and diarization while addressing ethical considerations. By the end of this book, you'll have an understanding of ASR technology and have the skills to implement Whisper. Moreover, Python coding examples will equip you to apply ASR technologies in your projects as well as prepare you to tackle challenges and seize opportunities in the rapidly evolving world of voice recognition and processing.
Table of Contents (16 chapters)
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1
Part 1: Introducing OpenAI’s Whisper
4
Part 2: Underlying Architecture
7
Part 3: Real-world Applications and Use Cases

Who this book is for

Learn OpenAI Whisper is designed for developers, data scientists, researchers, and business professionals who want to gain practical insights into leveraging OpenAI’s Whisper for ASR tasks.

The three primary personas who are the target audience of this book are as follows:

  • ASR enthusiasts: Individuals who are passionate about exploring the potential of advanced speech recognition technologies and want to stay abreast of the latest developments in the field
  • Developers and data scientists: Professionals who want to integrate Whisper into their projects, enhance existing applications with speech recognition capabilities, or build new solutions from scratch
  • Researchers and academics: Individuals in academia or research institutions interested in studying Whisper’s inner workings, conducting experiments, and pushing the boundaries of ASR technology

Throughout the book, readers will learn how to set up Whisper, fine-tune it for specific domains and languages, and apply it to real-world scenarios. They will gain a comprehensive understanding of Whisper’s architecture, features, and best practices for effective implementation.

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