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Learn OpenAI Whisper

You're reading from   Learn OpenAI Whisper Transform your understanding of GenAI through robust and accurate speech processing solutions

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781835085929
Length 372 pages
Edition 1st Edition
Concepts
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Author (1):
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Josué R. Batista Josué R. Batista
Author Profile Icon Josué R. Batista
Josué R. Batista
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Table of Contents (16) Chapters Close

Preface 1. Part 1: Introducing OpenAI’s Whisper FREE CHAPTER
2. Chapter 1: Unveiling Whisper – Introducing OpenAI’s Whisper 3. Chapter 2: Understanding the Core Mechanisms of Whisper 4. Part 2: Underlying Architecture
5. Chapter 3: Diving into the Whisper Architecture 6. Chapter 4: Fine-Tuning Whisper for Domain and Language Specificity 7. Part 3: Real-world Applications and Use Cases
8. Chapter 5: Applying Whisper in Various Contexts 9. Chapter 6: Expanding Applications with Whisper 10. Chapter 7: Exploring Advanced Voice Capabilities 11. Chapter 8: Diarizing Speech with WhisperX and NVIDIA’s NeMo 12. Chapter 9: Harnessing Whisper for Personalized Voice Synthesis 13. Chapter 10: Shaping the Future with Whisper 14. Index 15. Other Books You May Enjoy

Understanding text-to-speech in voice synthesis

TTS is a crucial component in the voice synthesis process, enabling speech to be generated from written text using the synthesized voice. Understanding the fundamentals of TTS is essential to grasp how voice synthesizing works and how it can be applied in various scenarios. Figure 9.1 illustrates a high-level overview of how TTS works in the context of voice synthesis without delving too deeply into technical specifics:

Figure 9.1 – The TTS voice synthesis pipeline

Figure 9.1 – The TTS voice synthesis pipeline

There are five components in the TTS voice synthesis pipeline:

  1. Text preprocessing:
    1. The input text is first normalized and preprocessed.
    2. Numbers, abbreviations, and special characters are expanded into full words.
    3. The text is divided into individual sentences, words, and phonemes (distinct sound units).
  2. Text-to-spectrogram:
    1. The normalized text is converted into a sequence of linguistic features and encoded into a vector representation...
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