What is text to speech? How modern conversational TTS works

Text-to-speech (TTS), or speech synthesis, converts written language into spoken audio and is used in accessibility tools, media production, navigation, phone systems, and increasingly AI voice agents. Modern neural TTS pipelines normalize written text, determine pronunciation through phonemes, model prosody such as pitch and timing, generate an audio waveform with a vocoder, and often stream the result in real time. TTS has evolved from robotic rule-based systems and recorded-snippet concatenation to neural and large speech models capable of expressive, controllable voices. Conversational TTS differs from traditional read-aloud applications because it must respond with very low time to first audio, begin speaking while language-model output is still arriving, handle short responses naturally, accurately read identifiers and numbers, and stop immediately when users interrupt. Voice quality is assessed through naturalness, intelligibility, latency, real-time generation speed, listener preference, pronunciation accuracy, pacing, consistency, and performance in real conversations rather than isolated samples. In voice agents, TTS operates alongside speech recognition, turn detection, and language models, making end-to-end reliability, interruption handling, streaming support, language coverage, control features, and cost important factors when selecting a system.

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