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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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Free Chapter
1
Part 1: Introducing OpenAI’s Whisper
4
Part 2: Underlying Architecture
7
Part 3: Real-world Applications and Use Cases

Diving into the Whisper Architecture

As we embark on the third chapter of our journey into the world of OpenAI’s Whisper, we’ll delve deeper into the architectural intricacies that underpin this advanced ASR system. This chapter, aptly titled Diving into the Whisper Architecture, is designed to provide a comprehensive understanding of the transformer model that forms the backbone of Whisper.

The transformer model, a concept that has revolutionized the field of machine learning, is a critical component of Whisper’s architecture. It is the engine that drives the system’s ability to convert spoken language into written text accurately. Understanding the transformer model is akin to understanding the heart of Whisper, and this chapter aims to guide you through its complexities with clarity and precision.

We’ll begin by introducing transformers and explaining their role and significance in the context of Whisper. We’ll provide a broad understanding...

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