AI Voice Cloning

alpha - wip

This project aims to clone a voice and use it to generate speech from written text. The goal is to create a proof of concept (PoC) where a user's voice is cloned and used to read text input.

Table of Contents

• Introduction
• Features
• Technology Stack
• Installation
• Usage
• Project Structure
• Data Collection
• Model Training
• Text-to-Speech Conversion
• Testing and Evaluation
• Deployment
• Best Practices
• License

Introduction

This project demonstrates how to clone a voice and generate speech using that cloned voice. The core idea is to train a Text-to-Speech (TTS) model on a dataset of recorded voice and use it to synthesize speech from text.

Features

• Voice Cloning
• Text-to-Speech (TTS) Conversion
• High-quality audio output
• Customizable and scalable deployment

Technology Stack

• Programming Language: Python
• Deep Learning Frameworks: PyTorch or TensorFlow
• Models:
  • Tacotron 2: For TTS
  • WaveGlow/MelGAN: For vocoder
• Pre-built Libraries/Frameworks:
  • Real-Time-Voice-Cloning or Coqui TTS

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/ai-voice-cloning.git
   cd ai-voice-cloning

2. Install the required Python packages:

   pip install -r requirements.txt

3. Set up any additional dependencies as required by the chosen framework or model.

Usage

1. Data Collection:

   • Record voice samples and save them in the data/raw directory.
   • Ensure each audio file is transcribed and aligned with the text.

2. Preprocess Data:

   • Run the preprocessing script to normalize audio and extract features.

   python preprocess.py