Text to Speech Model

Text-to-speech (TTS) models aim to synthesize natural-sounding human speech from text input, focusing on improving both the quality and controllability of generated audio. Current research emphasizes enhancing model architectures like Transformers and diffusion models, incorporating techniques such as preference alignment, adversarial training, and hierarchical acoustic modeling to achieve higher fidelity, speaker consistency, and emotional expressiveness. These advancements are significant for applications ranging from accessibility tools for the visually impaired to personalized voice assistants and improved synthetic data generation for other AI tasks.