Summary

In this chapter, we explored PVS using OpenAI’s Whisper. We discovered how to harness its power to create customized voice models that capture the unique characteristics of a voice or entirely new voices, opening a wide range of exciting applications.

We began by exploring the fundamentals of TTS in voice synthesis, gaining insights into the role of neural networks, audio processing, and voice synthesis. We learned how to convert audio files into the LJSpeech format, a standardized dataset structure commonly used in TTS tasks, using the OZEN Toolkit and Whisper. This hands-on experience provided a solid foundation for the subsequent steps in the voice synthesizing process.

Next, we delved into the DLAS toolkit, a robust framework for fine-tuning PVS models. We learned how to set up the training environment, prepare the dataset, and configure the model architecture. By leveraging Whisper’s accurate transcriptions, we aligned audio segments with their corresponding...