Streaming TTS Synthesis
TTS: Text-to-Speech
Overview
Streaming text-to-speech studies how to turn incoming text into speech before the full utterance is available, enabling responsive assistants and live voice interaction. Common approaches use causal or limited-lookahead models, text-speech alignment and interleaving, and autoregressive, codec-based, or diffusion decoders with bounded context and cached state. Acceleration methods such as multi-token prediction, distillation, speculative decoding, and optimized inference aim to lower first-audio latency while preserving intelligibility, speaker identity, and expressive prosody. A central challenge is balancing fast output with natural phrasing and continuity, especially when text is uncertain or long-form and when systems must support interruption and precise control of emotion or speaking rate.
Latest papers
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