Text-to-Speech
Safetensors
GGUF
qwen2
audio
speech
speech-language-models
conversational
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---
license: apache-2.0
pipeline_tag: text-to-speech
tags:
- audio
- speech
- speech-language-models
datasets:
- amphion/Emilia-Dataset
- neuphonic/emilia-yodas-english-neucodec
---

# NeuTTS Air ☁️ 

[![NeuTTSAir_Intro](neutts-air.png)](https://www.youtube.com/watch?v=YAB3hCtu5wE)

[🚀 Spaces Demo](https://huggingface.co/spaces/neuphonic/neutts-air), [🔧 Github](https://github.com/neuphonic/neutts-air)

[Q8 GGUF version](https://huggingface.co/neuphonic/neutts-air-q8-gguf), [Q4 GGUF version](https://huggingface.co/neuphonic/neutts-air-q4-gguf)

*Created by [Neuphonic](http://neuphonic.com/) - building faster, smaller, on-device voice AI*

State-of-the-art Voice AI has been locked behind web APIs for too long. NeuTTS Air is the world’s first super-realistic, on-device, TTS speech language model with instant voice cloning. Built off a 0.5B LLM backbone, NeuTTS Air brings natural-sounding speech, real-time performance, built-in security and speaker cloning to your local device - unlocking a new category of embedded voice agents, assistants, toys, and compliance-safe apps.

## Key Features

- 🗣Best-in-class realism for its size - produces natural, ultra-realistic voices that sound human
- 📱Optimised for on-device deployment - provided in GGML format, ready to run on phones, laptops, or even Raspberry Pis
- 👫Instant voice cloning - create your own speaker with as little as 3 seconds of audio
- 🚄Simple LM + codec architecture built off a 0.5B backbone - the sweet spot between speed, size, and quality for real-world applications


> [!CAUTION]
> Websites like neutts.com are popping up and they're not affliated with Neuphonic, our github or this repo.
>
> We are on neuphonic.com only. Please be careful out there! 🙏


## Model Details

NeuTTS Air is built off Qwen 0.5B - a lightweight yet capable language model optimised for text understanding and generation - as well as a powerful combination of technologies designed for efficiency and quality:

- **Audio Codec**: [NeuCodec](https://huggingface.co/neuphonic/neucodec) - our proprietary neural audio codec that achieves exceptional audio quality at low bitrates using a single codebook
- **Format**: Available in GGML format for efficient on-device inference
- **Responsibility**: Watermarked outputs
- **Inference Speed**: Real-time generation on mid-range devices
- **Power Consumption**: Optimised for mobile and embedded devices

## Get Started with NeuTTS

1. **Install System Dependencies (required): `espeak-ng`**

> [!NOTE]
> With `brew` on macOS Ventura and later, `apt` in Ubuntu version 25 or Debian version 13, and `choco`/`winget` on Windows, install the latest version of `espeak-ng` with the commands below. If you have a different or older operating system, you may need to install from source: see the following link https://github.com/espeak-ng/espeak-ng/blob/master/docs/building.md

   Please refer to the following link for instructions on how to install `espeak-ng`:

   https://github.com/espeak-ng/espeak-ng/blob/master/docs/guide.md

   ```bash
   # Mac OS
   brew install espeak-ng

   # Ubuntu/Debian
   sudo apt install espeak-ng

   # Windows install
   # via chocolatey (https://community.chocolatey.org/packages?page=1&prerelease=False&moderatorQueue=False&tags=espeak)
   choco install espeak-ng
   # via winget
   winget install -e --id eSpeak-NG.eSpeak-NG
   # via msi (need to add to path or folow the "Windows users who installed via msi" below)
   # find the msi at https://github.com/espeak-ng/espeak-ng/releases
   ```

   Windows users who installed via msi / do not have their install on path need to run the following (see https://github.com/bootphon/phonemizer/issues/163)
   ```pwsh
   $env:PHONEMIZER_ESPEAK_LIBRARY = "c:\Program Files\eSpeak NG\libespeak-ng.dll"
   $env:PHONEMIZER_ESPEAK_PATH = "c:\Program Files\eSpeak NG"
   setx PHONEMIZER_ESPEAK_LIBRARY "c:\Program Files\eSpeak NG\libespeak-ng.dll"
   setx PHONEMIZER_ESPEAK_PATH "c:\Program Files\eSpeak NG"
   ```

2. **Install NeuTTS**
   ```bash
   pip install neutts
   ```

   Or for a local editable install, clone the [neutts repository](https://github.com/neuphonic/neutts) and run in the base folder:
   ```bash
   pip install -e .
   ```

   Alternatively to install all dependencies, including `onnxruntime` and `llama-cpp-python` (equivalent to steps 3 and 4 below):

   ```bash
   pip install neutts[all]
   ```

   or for an editable install:

   ```bash
   pip install -e .[all]
   ```

3. **(Optional) Install `llama-cpp-python` to use `.gguf` models.**

   ```bash
   pip install "neutts[llama]"
   ```

   Note that this installs `llama-cpp-python` without GPU support. To install with GPU support (e.g., CUDA, MPS) please refer to:
   https://pypi.org/project/llama-cpp-python/

4. **(Optional) Install `onnxruntime` to use the `.onnx` decoder.**
   ```bash
   pip install "neutts[onnx]"
   ```

    

## **Basic Example**

Run the basic example script to synthesize speech:

```bash
python -m examples.basic_example \
  --input_text "My name is Dave, and um, I'm from London" \
  --ref_audio samples/dave.wav \
  --ref_text samples/dave.txt

```

To specify a particular model repo for the backbone or codec, add the `--backbone` argument. Available backbones are listed in [NeuTTS-Air huggingface collection](https://huggingface.co/collections/neuphonic/neutts-air-68cc14b7033b4c56197ef350).

Several examples are available, including a Jupyter notebook in the `examples` folder.

### **Simple One-Code Block Usage**

```python
from neutts import NeuTTS
import soundfile as sf

tts = NeuTTS(backbone_repo="neuphonic/neutts-air-q4-gguf", backbone_device="cpu", codec_repo="neuphonic/neucodec", codec_device="cpu")
input_text = "My name is Dave, and um, I'm from London."

ref_text = "samples/dave.txt"
ref_audio_path = "samples/dave.wav"

ref_text = open(ref_text, "r").read().strip()
ref_codes = tts.encode_reference(ref_audio_path)

wav = tts.infer(input_text, ref_codes, ref_text)
sf.write("test.wav", wav, 24000)

```

# Tips

NeuTTS Air requires two inputs:

1. A reference audio sample (`.wav` file)
2. A text string

The model then synthesises the text as speech in the style of the reference audio. This is what enables NeuTTS Air’s instant voice cloning capability.

### Example Reference Files

You can find some ready-to-use samples in the `examples` folder:

- `samples/dave.wav`
- `samples/jo.wav`

### Guidelines for Best Results

For optimal performance, reference audio samples should be:

1. **Mono channel**
2. **16-44 kHz sample rate**
3. **3–15 seconds in length**
4. **Saved as a `.wav` file**
5. **Clean** — minimal to no background noise
6. **Natural, continuous speech** — like a monologue or conversation, with few pauses, so the model can capture tone effectively

# **Responsibility**

Every audio file generated by NeuTTS Air includes [**Perth (Perceptual Threshold) Watermarker](https://github.com/resemble-ai/perth).**

# **Disclaimer**

Don't use this model to do bad things… please.