Readme
Inworld Realtime TTS 1.5 Max is Inworld’s flagship realtime text-to-speech model, offering the best balance of quality and speed. With <200ms median latency and support for 15 languages, it delivers the most natural, expressive speech for demanding applications.
Ranked #1 on Artificial Analysis, Inworld Realtime TTS delivers natural, expressive speech at a fraction of the cost of alternatives.
Key features
- <200ms median latency: Fast enough for real-time applications
- Highest quality: Best expressiveness and naturalness among Inworld 1.5 models
- 15 languages: English, Chinese, Japanese, Korean, Russian, Italian, Spanish, Portuguese, French, German, Polish, Dutch, Hindi, Hebrew, and Arabic
- Emotion control: Add emotion markups like
[happy],[sad],[angry]to control delivery - Non-verbal sounds: Insert
[laugh],[sigh],[cough]and other vocalizations - SSML pauses: Use
<break time="1s" />to insert natural pauses - Multiple formats: MP3, WAV, OGG Opus, and FLAC output
Voices
| Voice | Description |
|---|---|
Ashley |
A warm, natural female voice |
Dennis |
Middle-aged man with a smooth, calm and friendly voice |
Alex |
Energetic and expressive mid-range male voice, with a mildly nasal quality |
Darlene |
Soothing, comforting Southern female voice, ideal for bedtime stories and narrations |
Set voice_id to one of these preset voices. Custom voices you clone in your own Inworld account are scoped to that account’s API key and aren’t usable here.
Audio markups
The model supports rich text markups for expressive speech:
- Emotions:
[happy],[sad],[angry],[surprised],[fearful],[disgusted] - Delivery styles:
[laughing],[whispering] - Non-verbal sounds:
[breathe],[clear_throat],[cough],[laugh],[sigh],[yawn] - Pauses:
<break time="1s" />,<break time="500ms" />
Choosing between Inworld Realtime TTS models
- Realtime TTS 1.5 Max: Best balance of quality and speed (<200ms) — best for applications where voice quality is the top priority
- Realtime TTS 1.5 Mini: Ultra-fast (~120ms), most cost-efficient — best for high-volume, latency-sensitive applications