Text to Speech Synthesis

Text-to-speech (TTS) synthesis aims to convert written text into natural-sounding speech, focusing on improving both the quality and efficiency of generated audio. Current research emphasizes developing faster and more lightweight models, often employing diffusion models, autoregressive methods, and transformer architectures, while also exploring techniques like post-training quantization to reduce computational demands. These advancements are significant for expanding access to speech technologies across diverse languages and resource-constrained environments, impacting fields ranging from accessibility tools to personalized communication systems.