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Learn OpenAI Whisper
Learn OpenAI Whisper

Learn OpenAI Whisper : Transform your understanding of GenAI through robust and accurate speech processing solutions

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Learn OpenAI Whisper

Part 1: Introducing OpenAI’s Whisper

This part introduces you to OpenAI’s Whisper, a cutting-edge automatic speech recognition (ASR) technology. You will gain an understanding of Whisper’s basic features and functionalities, including its key capabilities and setup process. This foundational knowledge will set the stage for a deeper exploration of the technology and its applications in real-world scenarios.

This part includes the following chapters:

  • Chapter 1, Unveiling Whisper – Introducing OpenAI’s Whisper
  • Chapter 2, Understanding the Core Mechanisms of Whisper
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Key benefits

  • Uncover the intricate architecture and mechanics behind Whisper's robust speech recognition
  • Apply Whisper's technology in innovative projects, from audio transcription to voice synthesis
  • Navigate the practical use of Whisper in real-world scenarios for achieving dynamic tech solutions
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

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.

Who is this book for?

Learn OpenAI Whisper is designed for a diverse audience, including AI engineers, tech professionals, and students. It's ideal for those with a basic understanding of machine learning and Python programming, and an interest in voice technology, from developers integrating ASR in applications to researchers exploring the cutting-edge possibilities in artificial intelligence.

What you will learn

  • Integrate Whisper into voice assistants and chatbots
  • Use Whisper for efficient, accurate transcription services
  • Understand Whisper's transformer model structure and nuances
  • Fine-tune Whisper for specific language requirements globally
  • Implement Whisper in real-time translation scenarios
  • Explore voice synthesis capabilities using Whisper's robust tech
  • Execute voice diarization with Whisper and NVIDIA's NeMo
  • Navigate ethical considerations in advanced voice technology
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Publication date, Length, Edition, Language, ISBN-13
Publication date : May 31, 2024
Length: 372 pages
Edition : 1st
Language : English
ISBN-13 : 9781835085929
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$12.95

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Product Details

Publication date : May 31, 2024
Length: 372 pages
Edition : 1st
Language : English
ISBN-13 : 9781835085929
Category :
Concepts :

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Table of Contents

15 Chapters
Part 1: Introducing OpenAI’s Whisper Chevron down icon Chevron up icon
Chapter 1: Unveiling Whisper – Introducing OpenAI’s Whisper Chevron down icon Chevron up icon
Chapter 2: Understanding the Core Mechanisms of Whisper Chevron down icon Chevron up icon
Part 2: Underlying Architecture Chevron down icon Chevron up icon
Chapter 3: Diving into the Whisper Architecture Chevron down icon Chevron up icon
Chapter 4: Fine-Tuning Whisper for Domain and Language Specificity Chevron down icon Chevron up icon
Part 3: Real-world Applications and Use Cases Chevron down icon Chevron up icon
Chapter 5: Applying Whisper in Various Contexts Chevron down icon Chevron up icon
Chapter 6: Expanding Applications with Whisper Chevron down icon Chevron up icon
Chapter 7: Exploring Advanced Voice Capabilities Chevron down icon Chevron up icon
Chapter 8: Diarizing Speech with WhisperX and NVIDIA’s NeMo Chevron down icon Chevron up icon
Chapter 9: Harnessing Whisper for Personalized Voice Synthesis Chevron down icon Chevron up icon
Chapter 10: Shaping the Future with Whisper Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9
(13 Ratings)
5 star 92.3%
4 star 7.7%
3 star 0%
2 star 0%
1 star 0%
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L. Pickett Jun 01, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
If you’re an OpenAI enthusiast—or if you simply want to learn more about the topic, "Learn OpenAI Whisper" by Josue Batista is an EXCELLENT book! To summarize, it’s the encyclopedia of artificial intelligence. I ordered this book because I wanted to take a “deeper dive” into the subject. Wow! Not only does Batista take you deeper, but he also takes you on a knowledge excursion!Batista provides you with a great overview and table of content. Each chapter is broken down into “bite size” chunks of information. He helps readers understand the basics of AI core functionalities. He also provides real-world applications and use cases. "Learn OpenAI Whisper" has absolutely everything about OpenAI that you can think of—and more! It’s also written for readers “on the go” because it has a remarkable index, which makes it easy to find exactly what you need.
Amazon Verified review Amazon
LinnieX Oct 26, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I am very impressed with the flow of this book. It’s accessible to anybody regardless of their level of understanding. The Arthur walks you through how to set everything using Collab notebooks which run great. There are also companion videos demonstrating any code you need to use. I was able to figure out how to take my speech and turn it into text starting in chapter 9 and am working on doing the opposite now as well. Very well written by a subject matter expert. Highly recommend to anyone interested in AVR tech! Comprehensive book that will help your AI journey.
Amazon Verified review Amazon
Sai Kaushik Soma Jul 06, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
🌟 Just finished reading this amazing book "Learn OpenAI Whisper" by Josué R BatistaThis book is a treasure trove for anyone looking to dive deep into the world of automatic speech recognition (ASR) with OpenAI's Whisper technology.🚀 Key Highlights:💫 Introduction to Whisper and ASR Fundamentals: It begins with a thorough introduction to Whisper and the basics of ASR, covering key capabilities such as speech-to-text conversion, multilingual support, and seamless integration into various applications. This sets a solid foundation for understanding Whisper's significance in the ASR landscape.💫 Core Mechanisms and Architecture of Whisper: The book delves into the technical intricacies of Whisper's architecture, explaining the transformer model, encoder-decoder mechanics, and multitasking capabilities. It provides a historical perspective on the evolution of ASR technologies, helping readers appreciate the advancements leading to Whisper.💫 Fine-tuning and Customization: A significant portion is dedicated to fine-tuning Whisper for specific domains and languages. This section guides readers through setting up the necessary environment, integrating diverse datasets, and tailoring Whisper’s predictions, making it particularly valuable for developers and researchers aiming to optimize performance.💫 Practical Applications of Whisper: The book explores Whisper’s practical applications in various contexts such as transcription services, voice assistants, chatbots, and accessibility tools. Detailed examples and case studies demonstrate how to leverage Whisper’s capabilities to enhance different applications, showcasing its versatility and transformative potential.💫 Advanced Techniques and Future Perspectives: The concluding section covers advanced topics like real-time speech recognition, speaker diarization with WhisperX and NVIDIA’s NeMo, and personalized voice synthesis. It also discusses future trends, potential enhancements, and ethical considerations, providing a comprehensive view of the evolving ASR landscape.🌈 Why It's a Must-Read: In the rapidly advancing field of ASR, staying ahead means gaining hands-on experience and a deep understanding of the latest technologies. This book offers both through a meticulously structured journey that is both enlightening and immensely practical.🔥 Whether you're looking to innovate with AI-powered speech recognition or enhance your application development skills, this book is your gateway. Highly recommended for developers, researchers, entrepreneurs, and anyone curious about the future of ASR technology and its potential to revolutionize various industries. This book is your key to unlocking the full potential of Whisper and advancing your expertise in AI-driven speech recognition.
Amazon Verified review Amazon
Nik Jun 02, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Learn OpenAI Whisper” by Josué R. Batista serves as a key resource for those exploring automatic speech recognition (ASR) and generative AI. This book dives into OpenAI’s Whisper, a leading ASR system. Batista’s writing style clarifies complex concepts, allowing readers of all technical backgrounds to understand.The book is organized into three main parts: 1. Introduction to Whisper: This section introduces Whisper’s basic features and functionalities, including setup and initial usage. Batista explains human vocalization and speech recognition intricacies, preparing readers for deeper exploration. 2. Understanding the Architecture: The book explores Whisper’s core mechanisms, including the transformer model and techniques for fine-tuning for specific domains and languages. The detailed explanation of training Whisper with weak supervision on large-scale data stands out. 3. Real-world Applications: The final part covers practical applications of Whisper, such as transcription services, voice assistants, accessibility features, and personalized voice synthesis. Advanced topics like real-time speech recognition and speaker diarization using WhisperX and NVIDIA’s NeMo add value.This book stands out for its coverage of both theoretical and practical aspects of ASR. Batista explains the technology behind Whisper and provides hands-on guidance for using the system via platforms like Google Colaboratory. The tutorials and code examples on GitHub help readers implement Whisper in real-world scenarios.Overall, “Learn OpenAI Whisper” is essential for developers, researchers, and anyone interested in speech recognition technology. Batista’s expertise and dedication to the subject make this book a valuable addition to any AI enthusiast’s library
Amazon Verified review Amazon
Subhasish Ghosh Sep 27, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I managed catching up on my reading and completed, "𝑳𝒆𝒂𝒓𝒏 𝑶𝒑𝒆𝒏𝑨𝑰 𝑾𝒉𝒊𝒔𝒑𝒆𝒓: 𝑻𝒓𝒂𝒏𝒔𝒇𝒐𝒓𝒎 𝒀𝒐𝒖𝒓 𝑼𝒏𝒅𝒆𝒓𝒔𝒕𝒂𝒏𝒅𝒊𝒏𝒈 𝒐𝒇 𝑮𝒆𝒏𝑨𝑰 𝑻𝒉𝒓𝒐𝒖𝒈𝒉 𝑹𝒐𝒃𝒖𝒔𝒕 𝒂𝒏𝒅 𝑨𝒄𝒄𝒖𝒓𝒂𝒕𝒆 𝑺𝒑𝒆𝒆𝒄𝒉 𝑷𝒓𝒐𝒄𝒆𝒔𝒔𝒊𝒏𝒈 𝑺𝒐𝒍𝒖𝒕𝒊𝒐𝒏𝒔" by Josué Batista, Packt.An excellent book, this is a hands-on guide for anyone looking to deep-dive and master OpenAI Whisper. What is OpenAI Whisper?✅ Whisper is a Transformer based Encoder-Decoder architecture model. Quintessentially, it is a sequence-to-sequence model.✅ Trained on > 5M hours of labeled data, Whisper provides a state-of-the-art automatic speech recognition (ASR) service.✅ Why is Whisper's output *phenomenally brilliant*? Owing to one simple but very important point: Each input speech segment is given attention by converting audio into a log-Mel spectrogram + processing it in 30-second chunks.✌️𝐓𝐚𝐫𝐠𝐞𝐭 𝐚𝐮𝐝𝐢𝐞𝐧𝐜𝐞: GenAI Developers, Data Scientists, AI Researchers, Tech Business Leaders, CSAs, Tech Evangelists.✅ 5 things that makes this book an excellent read:💥Learn how to set up and use Whisper for transcription💥Understand the transformer model powering Whisper💥Fine-tune Whisper models for domain and language specificity💥Apply Whisper in voice assistants, accessibility, and more💥Use advanced techniques like quantization, speech synthesis, and speaker diarizationBonus:- Book includes 19 Python Google Colab notebooks with numerous hands-on examples and accompanying Code-In-Action videos, ensuring a practical and engaging learning experience.
Amazon Verified review Amazon
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