Neuvoice — Fast, On-Device Neural TTS by Lamapi

Neuvoice is a lightweight, on-device text-to-speech library that runs entirely via ONNX Runtime — no cloud calls, no latency surprises. (supertonic-3) Modified by Lamapi, it ships with a curated voice library and supports 31 languages out of the box.

Architecture:

Examples (Using 'Linda' Voice)

Turkish

<happy> Bugün kendimi mutlu hissediyorum!

English

<happy> I feel happy today!

French

<happy> Je me sens heureux aujourd'hui!

Japanese

<happy> こんにちは！今日はいい天気ですね。

Quick Start

pip install neuvoice

from neuvoice import TTS

tts = TTS(auto_download=True)
style = tts.get_voice_style("Alina")

text = "Hello! Welcome to Neuvoice — fast, private, on-device speech synthesis."
wav, duration = tts.synthesize(text, voice_style=style, lang="en")

tts.save_audio(wav, "output.wav")
print(f"Generated {duration:.2f}s of audio")

On first run, model assets are downloaded and cached automatically under ~/.cache/neuvoice.

Highlights

31 supported languages. Covers a wide range of scripts and regions, from European languages to Arabic, Hindi, Japanese, Korean, Vietnamese, and more.

Runs entirely on-device. ONNX Runtime powers inference — no API keys, no network dependency after the initial model download. CPU is sufficient; GPU acceleration is supported when available.

Rich voice library. Ships with voices including Alina, Cem, Cole, Giray, Leon, Lina, Linda, Mustafa, Sarp, Selin, Sema, and Soras. Each voice is a compact style embedding — load any of them by name in a single call.

Inline expression tags. Embed <happy>, <laugh>, <breath>, <sad>, and other tags directly in your text to shape the delivery without any extra parameters.

Long-form synthesis. Inputs are automatically chunked, synthesized, and rejoined with configurable silence — no manual splitting required.

Supported Languages

Available Voices

tts = TTS()
print(tts.voice_style_names)
# ['Alina', 'Cem', 'Cole', 'Giray', 'Leon', 'Lina', 'Linda',
#  'Mustafa', 'Sarp', 'Selin', 'Sema', 'Soras']

Load any voice by name:

style = tts.get_voice_style("Selin")

Or from a custom style file:

style = tts.get_voice_style_from_path("/path/to/my_voice.json")

synthesize() Parameters

Returns: (waveform, duration) — waveform as a (1, samples) NumPy array, duration in seconds.

Examples

Multilingual synthesis:

tts = TTS()
style = tts.get_voice_style("Leon")

pairs = [
    ("Merhaba! Bugün hava çok güzel.", "tr"),
    ("Bonjour! Il fait beau aujourd'hui.", "fr"),
    ("こんにちは！今日はいい天気ですね。", "ja"),
]
for text, lang in pairs:
    wav, dur = tts.synthesize(text, voice_style=style, lang=lang)
    tts.save_audio(wav, f"output_{lang}.wav")

Expression tags:

style = tts.get_voice_style("Lina")
text = "Good news! <happy> We just shipped the feature. <laugh> Don't tell anyone yet."
wav, dur = tts.synthesize(text, voice_style=style, lang="en")

Higher quality with more steps:

wav, dur = tts.synthesize(
    text="A slow, deliberate reading for maximum clarity.",
    voice_style=style,
    total_steps=30,
    speed=0.9,
    lang="en",
)

Configuration

Model cache location and thread counts can be controlled via environment variables:

License

Neuvoice is released under the MIT License. See LICENSE for details.

The bundled ONNX model is released under the OpenRAIL-M License.

Copyright © 2026 Lamapi

(NeuVoice by Lamapi is an open-source multilingual AI text-to-speech model focused on realistic voice synthesis, Turkish TTS, low-latency inference, and local/offline deployment on Hugging Face)