Audiobook Maker v3

This application utilizes open-source deep-learning text-to-speech and speech-to-speech models to create audiobooks. The main goal of the project is to be able to seamlessly create high-quality audiobooks by using these advancements in machine learning/AI.

It's designed for Windows, but pyside6 should be able to run on linux.

Table of Contents

• Features
• What changed from v1 and v2?
  • As a user?
  • As a developer?
• Windows Package Installation
• Manual Installation Windows 10/11
• Usage
• Acknowledgements

Install Specific Engines

• TortoiseTTS Installation
• RVC Installation

Features

✔️ Multi-speaker generation, allowing you to change who speaks which sentence etc.

✔️ Audio playback of individually generated sentences, or playback all to listen as it generates

✔️ Stopping during generation to pick up later, continuing to continue where you stopped from

✔️ Bulk sentence regeneration and editting in case you want to regenerate audio for a sentence or change which speaker is being used for a sentence

✔️ Reloading previous audiobooks and exporting audiobooks

✔️ Sentence remapping in case you need to update the original text file that was used for generation

✔️ Integration with popular open-source models like TortoiseTTS, RVC, StyleTTS (to be added), and XTTS (to be added)

What changed from v1 and v2?

As a user?

The biggest thing would be the ability to use multiple speakers, regenerate in bulk, and to stop during generation. It still fulfills pretty much the same stuff as before.

As a developer?

A lot. Pretty much the entire codebase was rewritten with the sole goal of making it more maintainable and more modular. This can be summarized in two points:

1. The most important: Completely removed any hardcoded parameters that referenced any TTS or S2S engine (tortoise/rvc)

   This makes it a (relavtive) breeze to add in any new TTS engines or S2S engine. You simply just need to create a configuration for that engine in the configs folder as all widgets in the GUI are created and handled dynamically, define a loading and generation procedure in the s2s or tts engines python file, and it'll work with very little to no issues. I designed it with the intention so that as long as the engine returns an audio_path back to the model.py, it will integrate just fine. I'll be writing documentation on how to do this so that I don't forget in the future, but it might be useful for anyone who want to fork this repo and build on it.

2. Moved over to MVC

   Point 1 wouldn't be as smooth without this. The previous implementation was heavily coupled together in one, ginormous class and that was getting too cramped and too messy to keep up with. So I moved over to something closer to an MVC framework and separated out the gui into view.py, the "brain" and logic into the controller.py, and all of the functional code into the model.py. Still messy, but not as messy as it would've been if I didn't switch over.

A minor change as well was the migration from pyqt5 --> pyside 6, but that wasn't too big of an issue. Small peculiar issues here and there, but nothing ground breaking.

I have decided to NOT use gradio for this. The biggest reason being that the previous versions were done in pyqt5. Another being my concern for limitations on customizability. I've done a fair share of work in gradio and I don't think that the way I want the audiobook maker to look and feel would be easily achievable by using it. And the last reason being I don't want a web interface or a local web server to be launched (maybe some users would run into issues with this). However, because I'm not using gradio, this also cannot be used on a cloud computer, so you will need all the hardware on your computer locally.

Windows Package Installation

Will be available for Youtube Channel Members at the Supporter (Package) level: https://www.youtube.com/channel/UCwNdsF7ZXOlrTKhSoGJPnlQ/join

Pre-requisites

• NVIDIA GPU with at least 8GB of VRAM (for heavier inference models like Tortoise, 4-6 GB might be possible as we're not training here)

1. Download the zip file provided to you on the members community tab.
2. Unzip the folder
3. Run the start.bat file

And that's it!

Manual Installation Windows 10/11

Pre-requistites

• Python 3.11: https://www.python.org/downloads/release/python-3119/
• git: https://git-scm.com/
• vscode (optional): https://code.visualstudio.com/
• ffmpeg: https://www.ffmpeg.org/download.html#build-windows
  • Watch a tutorial here: https://www.youtube.com/watch?v=JR36oH35Fgg&t=159s&ab_channel=Koolac
• NVIDIA GPU with at least 8GB of VRAM (for heavier inference models like Tortoise, 4-6 GB might be possible as we're not training here)

GUI Installation

1. Clone the repository and cd into it.

   git clone https://github.com/JarodMica/audiobook_maker.git
   cd audiobook_maker
   

2. Create a venv in python 3.11 and then activate it. If you can't activate the python venv due to restricted permissions: https://superuser.com/questions/106360/how-to-enable-execution-of-powershell-scripts

   py -3.11 -m venv venv
   .\venv\Scripts\activate
   

3. Install basic requirements to get the GUI opening

   pip install -r .\requirements.txt
   

4. Launch the interface

   python .\src\controller.py
   

5. (Optional) I recommend you create a batch script to launch the gui instead of manually doing it each time. Open notepad, throw the code block below into it, name it start.bat, and it should be fine. Make sure your extensions are showing so that it's not start.bat.txt

   call venv\Scripts\activate
   python webui.py
   

Congrats, the GUI can be launched! You should see in the errors in the terminal such as Tortoise not installed or RVC not installed

If you use it like this, you will only be able to use pyttsx3. To install additional engines, refer to the sections below to get the engines you want installed, I recommend you do all of them.

Text-to-Speech Engines

TortoiseTTS Installation

0. Make sure your venv is still activated, if not, activate it:

   .\venv\Scripts\activate
   

1. Clone the tortoise tts api repo, then pull its submodules:

   git clone https://github.com/JarodMica/tortoise_tts_api.git
   cd .\tortoise_tts_api\
   git submodule init
   git submodule update --remote
   

2. Install the submodules:

   pip install modules\tortoise_tts
   pip install modules\dlas
   

3. Install the tortoise tts api repo, then cd back to root:

   pip install .
   cd ..
   

4. Remove the tortoise_tts_api repo to not cause any conflicts with the actual library. If this fails, just simply delete the folder.

   rm -r -fo .\tortoise_tts_api\
   

5. Ensure you have pytorch installed with CUDA enabled. You may have gotten it from the previous library installations, so we want to be sure we're on the right version so do:

   pip uninstall torch -y
   pip install torch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 --index-url https://download.pytorch.org/whl/cu121
   

   Torch is a pretty large download, so it may take a bit of time. Once you have it installed here, it should be fine following the other install. However, sometimes, newer versions of torch may uninstall the one we just did, so you may need to uninstall and reinstall after each engine to make sure you have the correction version. After the first install, it will have been cached, so you won't have to wait each time afterwards.

Speech-to-Speech Engines

RVC Installation

0. Make sure your venv is still activated, if not, activate it:

   .\venv\Scripts\activate
   

1. Install the rvc-python library:

   pip install git+https://github.com/JarodMica/rvc-python
   

2. Install fairseq as a wheels file. Either download it from this link here https://huggingface.co/Jmica/rvc/resolve/main/fairseq-0.12.4-cp311-cp311-win_amd64.whl?download=true and place it in the audiobook_maker folder or run the two commands below:

   curl -Uri "https://huggingface.co/Jmica/rvc/resolve/main/fairseq-0.12.4-cp311-cp311-win_amd64.whl?download=true" -OutFile "fairseq-0.12.4-cp311-cp311-win_amd64.whl"
   pip install .\fairseq-0.12.4-cp311-cp311-win_amd64.whl
   

   It's done this way due to issues with fairseq on python 3.11 and above so I've compiled a wheels file for you to use. You can delete it afterwards if you want.
3. Check torch and make sure it's Version: 2.3.1+cu121. If it is, you're good to go. If not, uninstall and reinstall as shown in Tortoise install

   pip show torch
   

Usage

To be written

Acknowledgements

This has been put together using a variety of open-source models and libraries. Wouldn't have been possible without them.

TTS Engines:

• Tortoise TTS: https://github.com/neonbjb/tortoise-tts
• StyleTTS: https://github.com/yl4579/StyleTTS2

S2S Engines:

• RVC: https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI
  • Installable RVC Library: https://github.com/daswer123/rvc-python