🎙️ Podcast AI

Generate professional, studio-quality podcasts from text scripts using high-performance AI voice models.

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📖 Table of Contents

• About The Project
• ✨ Key Features
• 🎧 Example Output
• 🚀 Getting Started
  • Prerequisites
  • Installation & Setup
• ▶️ Usage
  • Basic Usage
  • Advanced Usage
• 📂 Project Structure
• 🤝 Contributing
• 📜 License
• 📧 Contact

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🤖 About The Project

Podcast AI is an open-source tool designed to automate audio content creation. It leverages the power of Piper TTS, a fast and high-quality neural text-to-speech system, with efficient ONNX models to transform plain text scripts into engaging, ready-to-publish podcasts.

Whether you're a content creator looking to streamline your workflow or a developer interested in AI-powered audio generation, this project provides a solid foundation.

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✨ Key Features

• ✅ High-Fidelity Speech Synthesis: Generates natural-sounding speech from text using state-of-the-art models.
• ✅ Fast & Efficient: Built on Piper TTS and ONNX Runtime for rapid, local inference without relying on cloud APIs.
• ✅ Customizable Voices: Easily switch between different voice models by providing the corresponding .onnx and .json files.
• ✅ Audio Assembly: Seamlessly combines generated speech segments, intro/outro music, and sound effects.
• ✅ Cross-Platform: Runs on any system with Python, including Windows, macOS, and Linux.
• ✅ Fully Open-Source: Free to use, modify, and distribute under the MIT License.

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🎧 Example Output

Listen to a sample podcast generated with this tool:

➡️ Listen to final_podcast.mp3

The audio was generated from a simple script like this:

(intro_music)
Welcome to AI Spotlight, the show where we explore the latest breakthroughs in artificial intelligence.
(transition_sound)
Today, we're discussing generative models. These models can create brand new content, from text and images to music and even code. It's a revolution in creativity.
(outro_music)

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🚀 Getting Started

Follow these steps to get the project running on your local machine.

Prerequisites

• Python 3.8+
• pip and venv (usually included with Python)
• git for cloning the repository

Installation & Setup

1. Clone the Repository

   git clone https://github.com/santhoshsharuk/podcast-ai.git
   cd podcast-ai

2. Download Core Dependencies & Voice Models Large files like the Piper engine and voice models are hosted on GitHub Releases to keep the repository lightweight.

   • Go to the Releases Page.
   • Download the latest piper.zip and the desired voice model (e.g., voice-en-us-amy-medium.zip).
   • Extract them into the project directory.

3. Organize Your Files Create a voices directory and place your model files inside. Your project structure should look like this:

   .
   ├── assemble_podcast.py
   ├── script.txt
   ├── voices/
   │   └── en_US-amy-medium/
   │       ├── en_US-amy-medium.onnx
   │       └── en_US-amy-medium.onnx.json
   ├── piper/
   │   ├── piper
   │   └── ... (other piper files)
   

4. Create a Virtual Environment & Install Requirements It's best practice to use a virtual environment to manage dependencies.

   # Create and activate the virtual environment
   python -m venv venv
   source venv/bin/activate  # On Windows, use: venv\Scripts\activate
   
   # Install the required Python packages
   pip install -r requirements.txt

You are now ready to generate your first podcast!

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▶️ Usage

The main script assemble_podcast.py reads your script.txt, generates audio for each line, and combines them into a final file.

Basic Usage

Simply run the script with Python:

python assemble_podcast.py

This will:

• Read script.txt.
• Use the default voice model found in the voices/ directory.
• Output the final audio to final_podcast.mp3.
• Play a success sound upon completion.

Advanced Usage

You can customize the behavior using command-line arguments for greater flexibility.

python assemble_podcast.py \
  --script my_new_episode.txt \
  --voice voices/en_GB-alan-medium \
  --output episode_01.wav \
  --no-sound

Available Arguments:

Argument	Shorthand	Description	Default
--script	-s	Path to the input script file.	script.txt
--voice	-v	Path to the voice model directory.	First directory in voices/
--output	-o	Path for the final output audio file.	final_podcast.mp3
--no-sound		Disable the success sound upon completion.	N/A (flag)

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📂 Project Structure

.
├── .gitignore              # Files to ignore for Git
├── assemble_podcast.py     # Main script to generate the podcast
├── LICENSE                 # Project license file
├── README.md               # You are here!
├── requirements.txt        # Python package dependencies
├── script.txt              # Default input text script
├── final_podcast.mp3       # Example output file
├── assets/                 # (Optional) For sounds like intros, outros
│   └── success.wav
├── piper/                  # Piper TTS engine (from releases)
└── voices/                 # Directory for voice models
    └── en_US-amy-medium/
        ├── en_US-amy-medium.onnx
        └── en_US-amy-medium.onnx.json

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🤝 Contributing

Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project (🍴)
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request (🚀)

Please open an issue first to discuss any major changes you would like to make.

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📜 License

This project is licensed under the MIT License. See the LICENSE file for more details.

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📧 Contact

Santhosh Sharuk

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Generated by Podcast AI - Where words find their voice.