Text2AudioBook

Project Summary

This project is a GUI-based application designed to convert text files into speech using OpenAI's text-to-speech (TTS) API. It is developed in Python and utilizes the Tkinter library for its graphical user interface. The primary goal of the application is to provide a user-friendly way to transform written text into spoken audio, making content more accessible and versatile.

Features

• Text to Speech Conversion: Converts text files to speech using the OpenAI API.
• Voice Selection: Allows users to choose from different voices for the TTS conversion.
• Text Chunking: Splits large text files into manageable chunks to ensure smooth processing and conversion.
• Logging: Logs the positions of text chunks and the sentences where each chunk starts.
• Output Management: Saves output audio files and chunk position logs to a specified directory.

Components

main.py

• Purpose: Serves as the main entry point of the application. Manages the GUI, user inputs, and initiates the text-to-speech conversion process.
• Functions:
  • read_api_key(file_path): Reads the OpenAI API key from a file.
  • select_file(): Opens a file dialog for selecting a text file.
  • select_output_folder(): Opens a directory dialog for selecting the output folder.
  • start_conversion(): Handles the text-to-speech conversion process, including reading text, splitting it into chunks, converting to speech, and saving outputs.
• GUI Elements: Includes fields for input file selection, output folder selection, output filename, and voice selection. Also includes buttons to browse files and start the conversion.
• Logging: Configures logging for tracking events and errors.
• Default Output Folder: Uses a default output folder named output if no output folder is specified by the user.

text_processing.py

• Purpose: Handles text processing tasks, including reading text from files and splitting text into chunks.
• Functions:
  • read_text_from_file(file_path): Reads the text content from a specified file.
  • split_text(text, max_length=3500): Splits the text into smaller chunks of up to 3500 characters, ensuring logical sentence breaks to avoid cutting sentences awkwardly.

tts_conversion.py

• Purpose: Manages the conversion of text chunks to speech and the concatenation of audio files.
• Functions:
  • convert_text_chunk_to_speech(chunk, index, api_key, voice, output_folder, timestamp): Converts a text chunk into speech using the OpenAI API and saves it as an MP3 file in the specified output folder.
  • convert_text_to_speech(text_chunks, api_key, voice, output_folder, timestamp): Converts multiple text chunks to speech in parallel using a thread pool and returns a list of audio file paths.
  • concatenate_audio_files(audio_files, output_file_path): Combines multiple MP3 files into a single MP3 file.

requirements.txt

• Purpose: Lists the necessary Python libraries required for the project.
• Dependencies:
  • requests
  • pydub
  • openai
  • moviepy

install_ffmpeg.py

• Purpose: Provides a script to automate the installation of FFmpeg, which is required for audio processing by pydub.
• Function:
  • install_ffmpeg(): Checks the operating system and installs FFmpeg accordingly. On Windows, it downloads and extracts FFmpeg, and updates the system PATH.

Goals

• Accessibility: Transform written text into spoken audio to make content more accessible.
• User-Friendly Interface: Provide a simple and intuitive GUI for users to perform text-to-speech conversion without needing to write code.
• Flexibility: Allow users to select different voices and manage large text files by splitting them into chunks.
• Logging and Output Management: Log chunk positions and starting sentences to help users understand how their text is processed. Save outputs to user-specified or default directories.

Installation and Setup

Step 1: Install Python Dependencies

Install the required Python libraries using pip:

pip install -r requirements.txt

Step 2: Install FFmpeg

FFmpeg is required for audio processing. Follow the instructions below to install it.

Windows

1. Download the latest FFmpeg build from the FFmpeg Builds Repository.
2. Extract the downloaded zip file.
3. Add the bin directory from the extracted folder to your system's PATH. This allows FFmpeg to be accessible from any command line.

macOS Use Homebrew to install FFmpeg:

brew install ffmpeg

Linux Use your package manager to install FFmpeg:

sudo apt update
sudo apt install ffmpeg

Step 3: Running the Application

Run the main application:

python main.py

Usage

Preparing Your Files

1. Save Your OpenAI API Key:

   • Ensure your OpenAI API key is saved in a file named key.txt within the project directory. This key is necessary for accessing the OpenAI API services.

2. Prepare Your Text File:

   • Save the text you want to convert into a file named input.txt in the project directory. This file will be used as the input for the text-to-speech conversion.

Running the Application

1. Launch the Application:

   • Run the main application by executing the following command in your terminal or command prompt:

   python main.py

2. Select a Text File:

   • In the application GUI, click the "Browse..." button next to the "Input Text File" field.
   • Navigate to and select the input.txt file or any other text file you want to convert.

3. Choose an Output Folder:

   • Click the "Browse..." button next to the "Output Folder" field.
   • Select the folder where you want to save the generated audio files and chunk positions file.
   • If you do not select an output folder, the application will use the default output folder in the project directory.

4. Enter the Desired Output File Name:

   • In the "Output File Name (without extension)" field, enter the desired name for your output file. Do not include any file extension (e.g., enter audiobook, not audiobook.mp3).

5. Select a Voice:

   • From the "Select Voice" dropdown menu, choose the voice you want to use for the text-to-speech conversion. Options include various synthetic voices provided by OpenAI.

6. Start the Conversion:

   • Click the "Start Conversion" button to begin the text-to-speech conversion process.
   • The application will process the text file, convert it to speech, and save the output audio file and chunk positions file in the specified output folder.
   • A message box will inform you when the conversion is complete and provide the location of the saved files.

Troubleshooting

• If you encounter issues with FFmpeg installation, ensure the bin directory is correctly added to your system's PATH.
• For Python dependency issues, verify that you are using the correct version of Python (3.7 or higher).

Contributing

We welcome contributions! Please fork the repository and create a pull request with your changes. Ensure your code adheres to the project's coding standards and includes appropriate tests.

License

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