Text-to-Speech Fine-tuning Tutorial - StyleTTS2 Voice Cloning and Model Adaptation

Dive into a comprehensive tutorial on fine-tuning text-to-speech models for voice cloning. Explore the fundamentals of text-to-speech technology, including transformers, diffusion networks, and generative adversarial networks. Learn about StyleTTS2, a powerful text-to-speech model, and understand the differences between voice cloning and fine-tuning. Gain practical knowledge on dataset preparation, fine-tuning processes in Colab and Jupyter Notebook, and performance evaluation. Discover tips for improving voice cloning results and understand the importance of loss functions in the training process. This in-depth video also covers materials, code, and scripts needed for implementation, making it an essential resource for those looking to master text-to-speech fine-tuning techniques.

Voice-cloning and fine-tuning text-to-speech models
Video Overview
Understanding text to speech models
Text to speech Transformers
Diffusion networks for text to speech
Generative Adversarial Networks for Text to Speech
Controlling style in text to speech models
StyleTTS2 Text to Speech
Voice cloning versus fine-tuning
Dataset preparation tips for voice cloning
Materials, Code, Scripts
Dataset preparation for StyleTTS fine-tuning in Colab
Fine-tuning StyleTTS2 in a Jupyter Notebook
Text to speech inference and performance
Understanding losses.
Voice Cloning performance without fine-tuning
Dataset and Fine-tuning tips
Trelis Internships