While speech-to-text brings human input into the digital realm, text-to-speech (TTS) gives voice to machines — completing the loop in conversational AI. From virtual assistants and bots to smart devices, TTS is the output stage in voice AI. It transforms text into natural-sounding audio that responds in real time.
But it’s more than just speaking. Today’s TTS must balance latency, emotion, clarity, and personalization — making your AI sound human, not robotic.
Text-to-speech (TTS) is no longer about reading text aloud. It’s a complex orchestration of emotion, latency, prosody, and real-time delivery. This blog explores what defines a good TTS model, how top providers compare, and what to expect in 2025.
Turbo v2 — rich in emotional range, TTFB: 300ms, Cost: $0.08/min
Flash v2 — faster and cheaper, TTFB: 170ms, Cost: $0.04/min
Note: Word timestamps are not available.
Even top-tier models struggle with acronyms or brand names. Use:
Use them to:
{ "word_timestamps": { "words": ["What's", "the", "capital"], "start": [0.02, 0.3, 0.48], "end": [0.3, 0.36, 0.6] } }
TTS for assistants must be:
Cartesia and Rime lead in streaming APIs today.
In 2025, TTS is a strategic choice. It affects how your product sounds — and how it’s felt. Real-time voice agents need models that are fast, expressive, and customizable.
Your voice is your brand. Make it speak smart.
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