RealtimeTTS

May 10, 2026 · View on GitHub

RealtimeTTS is a Python text-to-speech library for applications that need to turn strings, generators, and LLM token streams into audio with low latency. It can play speech locally, stream chunks to another process, write WAV files, and fall back across multiple engines.

The project supports a broad engine matrix: local system voices, cloud APIs, free service wrappers, local neural models, and voice-cloning stacks.

Install

For the fastest local smoke test, install the system engine:

pip install "realtimetts[system]"

On Linux, install PortAudio headers before installing PyAudio:

sudo apt-get update
sudo apt-get install python3-dev portaudio19-dev

On macOS:

brew install portaudio

For cloud engines, local neural engines, CUDA, mpv, and current packaging caveats, see docs/installation.md.

First Audio

from RealtimeTTS import TextToAudioStream, SystemEngine


if __name__ == "__main__":
    stream = TextToAudioStream(SystemEngine())
    stream.feed("Hello from RealtimeTTS.")
    stream.play()

Use the if __name__ == "__main__": guard in scripts, especially on Windows and when using engines that start worker processes.

Streaming Text

feed() accepts an iterator, so text can arrive while audio is already playing:

from RealtimeTTS import TextToAudioStream, SystemEngine


def text_chunks():
    yield "This starts speaking quickly. "
    yield "More text can arrive while audio is already playing."


if __name__ == "__main__":
    stream = TextToAudioStream(SystemEngine())
    stream.feed(text_chunks())
    stream.play()

Use the same pattern with an LLM client by yielding only non-empty text chunks. See docs/llm-streaming.md.

Output

Write audio to a WAV file without local speaker playback:

from RealtimeTTS import TextToAudioStream, SystemEngine


if __name__ == "__main__":
    stream = TextToAudioStream(SystemEngine())
    stream.feed("Save this speech to a file.")
    stream.play(output_wavfile="speech.wav", muted=True)

For output devices, mpv playback, muted mode, callbacks, and chunk formats, see docs/output-and-files.md.

Features

Low-latency playback from strings, generators, and streamed model output.
Multiple engines with local, cloud, free-service, and neural model options.
Fallback engines for more resilient synthesis.
Sync and async playback with pause, resume, stop, and state inspection.
Text, audio, sentence, character, word-timing, and audio-chunk callbacks.
WAV output, muted synthesis, selected output devices, and volume control.
Voice switching and voice-cloning workflows where supported by the engine.

Engine Overview

Engine	Type	Install/status note	Best first use
`SystemEngine`	Local	`realtimetts[system]`	First local audio smoke test.
`GTTSEngine`	Free service	`realtimetts[gtts]`	Simple network-backed speech.
`EdgeEngine`	Free service	`realtimetts[edge]`, needs `mpv`	Free streamed voices.
`OpenAIEngine`	Cloud API	`realtimetts[openai]`	OpenAI TTS voices.
`AzureEngine`	Cloud API	`realtimetts[azure]`	Azure voices and word timings.
`ElevenlabsEngine`	Cloud API	`realtimetts[elevenlabs]`, needs `mpv`	High-quality API voices.
`CambEngine`	Cloud API	`realtimetts[camb]`	CAMB MARS API voices.
`MiniMaxEngine`	Cloud API	`realtimetts[minimax]`	MiniMax cloud voices.
`CartesiaEngine`	Cloud API	`realtimetts[cartesia]`	Cartesia API voices.
`TypecastEngine`	Cloud API	`realtimetts[typecast]`	Typecast API voices.
`ModelsLabEngine`	Cloud API	`realtimetts[modelslab]`, root export pending	ModelsLab API voices.
`CoquiEngine`	Local neural	`realtimetts[coqui]`	Local XTTS voice cloning.
`PiperEngine`	Local executable	`realtimetts[piper]`, external Piper setup	Fast local executable TTS.
`StyleTTSEngine`	Local neural	`realtimetts[styletts]`, local checkout/assets	StyleTTS experiments.
`ParlerEngine`	Local neural	`realtimetts[parler]`	GPU local model experiments.
`KokoroEngine`	Local neural	`realtimetts[kokoro]`	Local voices and timing support.
`OrpheusEngine`	Local/API-style	`realtimetts[orpheus]`	Orpheus model workflows.
`FasterQwenEngine`	Local neural	`realtimetts[qwen]`	Qwen voice cloning.
`OmniVoiceEngine`	Local neural	`realtimetts[omnivoice]`	Multilingual voice cloning.
`PocketTTSEngine`	Local lightweight	`realtimetts[pockettts]`	CPU-oriented voice cloning.
`NeuTTSEngine`	Local neural	`realtimetts[neutts]`, optional `neutts-gguf`	Reference-audio voice cloning.
`ZipVoiceEngine`	Local neural	`realtimetts[zipvoice]`, external checkout	ZipVoice cloning/server demos.
`LuxTTSEngine`	Local neural	`realtimetts[luxtts]`	LuxTTS voice cloning.
`ChatterboxEngine`	Local neural	`realtimetts[chatterbox]`	Chatterbox prompt-audio voices.
`SoproTTSEngine`	Local neural	`realtimetts[sopro]`	Sopro reference-audio voices.
`SopranoEngine`	Local neural	`realtimetts[soprano]`	Soprano local synthesis.
`MossTTSEngine`	Local neural	`realtimetts[moss]`, runtime assets	MOSS-TTS experiments.

See docs/engine-selection.md before choosing an engine for an application. The engine-specific docs are being split out from the old README and source audit.

Documentation

Quick start: shortest working examples.
Installation: extras, platform setup, external tools, API keys, and known packaging mismatches.
Engine selection: engine matrix and selection guidance.
Feed and playback: feed(), play(), play_async(), pause, resume, stop, text state, and inline tags.
LLM streaming: provider-neutral streamed text patterns and latency tuning.
Output and files: WAV files, audio chunks, muted mode, output devices, mpv, buffering, and volume.
Engine setup pages now link one focused page for each concrete engine source.
FAQ: legacy troubleshooting page while topic docs are being split out.

Legacy translated docs remain under docs/<locale>/ while English is refactored as the canonical source.

Server Example

The browser and WebSocket server example lives in example_fast_api/:

python -m pip install fastapi uvicorn websockets pyaudio
python example_fast_api/async_server.py

Open http://localhost:8000 or connect to ws://localhost:8000/ws.

RealtimeSTT is the speech-to-text counterpart for realtime voice input.

Contributing

Focused docs, tests, and engine fixes are easiest to review. During the docs refactor, keep English docs canonical and note mismatches between source, packaging, examples, and tests rather than hiding them.

License

RealtimeTTS source code is MIT licensed. Engine providers, model weights, voice data, datasets, generated audio, and third-party services can have separate terms. Read LICENSING_ADDENDUM.md and the relevant provider or model licenses before commercial use.

Audio samples derived from the EARS dataset by Meta are licensed under CC BY-NC 4.0. See the original dataset terms for details.

Author

Kolja Beigel