VoxPocket Khmer TTS

VoxPocket Khmer TTS

Turns Khmer text into speech in the browser, with voice cloning from a short clip, optional styles and voice design from a description. For creators and researchers working with Khmer audio.

Made by muyleanging on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.

About

What it is: VoxPocket turns Khmer text into spoken audio in your browser. You can clone a voice from a short audio clip, add a style to it, or design a voice from a written description. It runs on the VoxPocket Khmer model from the same author.

Who it suits: It suits people who need Khmer speech without recording it themselves, and people curious about small speech models.

Industry | Who uses it | How they use it | Example
Media | Video creators | Add Khmer narration to clips | Read a short script aloud in a chosen voice
Education | Teachers and course makers | Make spoken versions of lessons | Turn a reading passage into audio for learners
App building | Developers | Hear how Khmer text sounds when read out | Check how a notice or label is spoken
Research | Speech researchers | Try a small Khmer voice model | Compare a voice made from a clip with one made from a description

You can skip it if you need speech in a language other than Khmer.

Where to use it:

• A web browser, on the Space's page at Hugging Face
• Your own computer, on Windows, macOS or Linux with Python

Use case | Who | What they get back
Narration | Creators | A Khmer voice-over from typed text
Styled voice | Creators | Audio in a cloned voice with a chosen style
Designed voice | Researchers | A new voice built from a written description

How to set it up:

• Nothing to install if you use the Space online
• Python, if you run a copy on your own computer
• The huggingface_hub package, installed with pip

1. Open the Space's page on Hugging Face to use it online.
2. To run a copy, install huggingface_hub and download the Space into a folder.
3. Move into that folder and install Gradio at the pinned version, then the listed packages.
4. Start the app with Python.

pip install -U huggingface_hub
hf download muyleanging/VoxPocket-TTS-Demo --repo-type space --local-dir VoxPocket-TTS-Demo
cd VoxPocket-TTS-Demo
pip install gradio==6.31.0
pip install -r requirements.txt
python app.py

How to use it: Enter your Khmer text, then choose how the voice is made. Either give a short clip to clone, add a style, or describe the voice you want. On your own copy, start the app with this command and open the local page Gradio prints.

python app.py

Example: Type a short Khmer greeting, add a few seconds of a voice you have the right to use, and run it. You get the greeting back as audio in a voice close to the clip.

For newcomers and experts: If you are new to this, open the Space online and try one short Khmer sentence first. Use your own voice clip, since that is the easiest voice to be sure you may use.

If you know the field, the repository holds app.py, a Khmer text helper, a lexicon file and a vocabulary file. That points to Khmer text preparation before the model speaks. The Space is built with Gradio and runs on GPU hardware at Hugging Face, so a copy on your own machine may be slow without one.

You enter Khmer text
You pick a clip, style or description
The VoxPocket model builds the voice
The audio plays back in the browser

Good to know:

• License: apache-2
• Cost to run: none named. The online Space runs on Hugging Face hardware, and a copy needs the Python packages in requirements.txt.
• Data it reaches: the text and audio clips you give it, and the model it names on Hugging Face.
• Not for: impersonating real people or making deceptive audio. Use only voices you have the right to use.

On Hugging Face, 13 November 2026

• Likes: 1
• Built with: gradio
• License: apache-2.0

Links

• Space: https://huggingface.co/spaces/muyleanging/VoxPocket-TTS-Demo
• Files: https://huggingface.co/spaces/muyleanging/VoxPocket-TTS-Demo/tree/main

Try it

Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.