Inworld TTS 1.5 Max is Inworld’s flagship 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 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 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 - Voice cloning: Use preset voices or bring your own cloned voice ID
- Multiple formats: MP3, WAV, OGG Opus, and FLAC output
Preset 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 |
You can also use custom cloned voice IDs from the Inworld platform. To browse all available voices, use the List Voices API or the TTS Playground.
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 TTS models
- TTS 1.5 Max: Best balance of quality and speed (<200ms) — best for applications where voice quality is the top priority
- TTS 1.5 Mini: Ultra-fast (~120ms), most cost-efficient — best for high-volume, latency-sensitive applications
Links
Model created
Model updated