realtimetts 0.7.0

Stream text into audio with an easy-to-use, highly configurable library delivering voice output with minimal latency.

To install realtimetts, you need to specify the TTS engine(s) you wish to use.

For example, to install all supported engines:

pip install realtimetts[all]

To install with the Coqui TTS engine:

pip install realtimetts[coqui]

Available engine options include:

• all: Install all supported engines
• system: Local system TTS via pyttsx3
• azure: Azure Speech Services support
• elevenlabs: ElevenLabs API integration
• openai: OpenAI TTS services
• gtts: Google Text-to-Speech
• edge: Microsoft Edge TTS
• coqui: Coqui TTS engine
• camb: CAMB AI MARS TTS
• minimax: MiniMax Cloud TTS
• cartesia: Cartesia API integration
• modelslab: ModelsLab API integration
• orpheus: Orpheus TTS support
• qwen: Faster Qwen3 TTS integration
• omnivoice: Omnivoice TTS integration
• luxtts: LuxTTS integration
• chatterbox: Chatterbox Turbo integration
• sopro: SoproTTS integration
• soprano: SopranoTTS integration
• neutts: NeuTTS integration
• zipvoice: ZipVoice dependency support
• moss: MOSS-TTS dependency support
• pockettts: PocketTTS integration
• parler: Parler TTS integration
• styletts: StyleTTS integration
• piper: Piper executable engine support
• typecast: Typecast API integration
• minimal: Core package only (for custom engine development)

You can install multiple engines by separating them with commas. For example:

pip install realtimetts[azure,elevenlabs,openai]

RealtimeTTS

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.

Project Status

RealtimeTTS is community-driven. Focused pull requests are welcome, while maintainer availability for new features and support may be limited.

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.
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.

Related Project

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