Clone Any Voice in Seconds with the Real-Time-Voice-Cloning Open‑Source TTS

Overview

Text‑to‑speech (TTS) converts written text into spoken audio. Modern deep‑learning TTS systems can synthesize speech that mimics a specific speaker when given a short voice sample.

Project

Real‑Time‑Voice‑Cloning is an open‑source deep‑learning voice synthesis project that can generate a voice clone in about five seconds after analyzing a short audio clip of the target speaker.

How it works

The system requires two inputs: the text to be spoken and a voice sample of the target speaker. The model extracts the speaker’s timbre and style from the sample, then synthesizes the requested text in that voice.

Installation

Clone the repository:

git clone https://github.com/CorentinJ/Real-Time-Voice-Cloning.git

Install the required Python packages (Python 3 is required): pip3 install -r requirements.txt Download the pretrained models and datasets as described in the repository’s README.

Running the demo

Launch the graphical demo toolbox with the following command (replace <datasets_root> with the path to your data folder): python demo_toolbox.py -d <datasets_root> The interface lets you load a voice sample, type any text, and generate the cloned speech. Example output includes sentences such as:

"Do you know the Toronto Raptors are basketball champions? Basketball is a great sport."

Additional features

You can click the “Random” button to randomize the voice input, then press “Load” to feed the new sample into the system.

Ethical considerations

The technology is powerful but can be misused for misinformation. Users should apply the tool responsibly and be aware of potential ethical implications.

Repository URL: https://github.com/CorentinJ/Real-Time-Voice-Cloning