Full Stack Text-to-Speech (TTS) Course For Beginners

Explore the essential components and techniques for converting text into speech.

• 1.1 Text Processing:
  • ‍Dive into text processing techniques such as tokenization and normalization, which are crucial for accurate speech synthesis.
• 1.2 Phonetics and Phonology:
  • Understand the basics of phonetics and phonology to effectively translate text into spoken words.
• 1.3 Prosody and Intonation:
  • Learn about the importance of prosody and intonation in making synthesized speech sound natural and human-like.
    

Learn various methods of speech synthesis and their applications.

• 1.1 Concatenative Synthesis:
  • ‍Explore how pre-recoreded speech units are concatenated to form complete utterances.
• 1.2 Formant Synthesis:‍
•               Understand how speech is generated by modeling the human vocal tract.

• 1.3 Parametric Synthesis:
  • Learn about the statistical modeling of speech sounds.
• 1.4 Neural Network-Based Synthesis:
  • Delve into modern techniques like neural TTS models for high-quality speech synthesis.
    

Get hands-on with popular TTS libraries and tools.

• 1.1 Overview of TTS Libraries:
  • ‍Learn about Google Text-to-Speech, Mozilla TTS, and other popular libraries.
• 1.2 Installation and Setup:
  • Set up your development environment to start working with TTS tools.

Implement a basic TTS system using the knowledge and tools acquired.

• 1.1 Text Preprocessing:
  • ‍Prepare text data for synthesis.
• 1.2 Selecting Synthesis Technique:
  • Choose the appropriate synthesis method for your project.
• 1.3 Generating Speech from Text:
  • Combine all components to create a functional TTS system.

Explore different types of voice models and their training processes.

• 1.1 Types of Voice Models:
  • ‍Learn about male, female, robotic, and other voice models.
• 1.2 Training Voice Models:
  • Understand the process of training voice models for high-quality speech synthesis.
• 1.3 Voice Quality and Naturalness:
  • Learn techniques to improve the naturalness of synthesized speech.

Utilize deep learning techniques to enhance TTS systems.

• 1.1 Introduction to Deep Learning for TTS:
  • ‍Understand the basics of using deep learning in TTS.
• 1.2 Sequence-to-Sequence Models:
  • Learn about models that convert sequences of text to sequences of speech.
• 1.3 Tacotron and Tacotron 2 Architectures:
  • Dive into advanced architecture for high-quality speech synthesis.

Implement a Tacotron model for a practical TTS project.

• 1.1Implementing Tacotron Model:
  • ‍Set up and implement a Tacotron model.
• 1.2 Training a TTS Model:
  • Train the model on a dataset to produce speech.
• 1.3 Generating Speech:
  • Use the trained model to convert text inputs into speech outputs.