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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

Understanding the transformer model in Whisper

In this section, we’ll explore how the transformer model empowered a breakthrough in NLP and understand its mechanics, enabling Whisper to accurately transform spoken utterances into written phrases. We’ll walk through the specifics of its encoder-decoder structure, along with its optimizations, making it unmatched for speech processing tasks. By the end, we’ll have insight into the inner workings of this advanced model architecture, comprehending how it drives Whisper’s prowess and unlocking applications across languages.

Introducing the transformer model

As an expert in OpenAI’s Whisper, I am often asked, “What makes this ASR system so advanced?” The answer lies in its backbone: the pioneering transformer model architecture. It all started with the paper Attention Is All You Need, by Vaswani et al., published in 2017. Introducing the transformer model marked a significant paradigm...

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