TTS Synthesis

Text-to-speech synthesis studies how to turn written language into speech while preserving words, pronunciation, and the intended voice and delivery. Systems range from autoregressive models that generate speech tokens in sequence to parallel methods such as flow matching and diffusion, often using speaker prompts, phonetic alignment, or prosody controls. Current work extends these methods to multilingual and low-resource languages, expressive speech, long-form output, and low-latency streaming. A central challenge is balancing intelligibility, naturalness, speaker identity, and fine-grained control, while evaluations based on overall quality scores may miss errors in pronunciation, accent, or context.