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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

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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