baxtor95/pdf-to-speech

PDF to Speech Converter

This tool converts PDF documents into spoken audio files using Google's Text-to-Speech (TTS) API. It's designed to be flexible and powerful, allowing batch processing, interactive selection, and resume capabilities.

Features

• Batch Processing: Convert all PDFs in a directory to audio files automatically.
• Interactive Mode: Select specific PDFs to convert via a simple interactive prompt.
• Resume Capability: Pick up processing where you left off, skipping over already processed files.
• Segmentation: Split large PDFs into manageable segments based on chapters or sections.
• Customizable Output: Choose from multiple audio formats and specify metadata like title and author.
• Language Detection: Automatically detect the language of the text to optimize TTS.
• Logging: Detailed logs for monitoring and debugging the processing workflow.

Prerequisites

Before you begin, ensure you have the following installed:

• Python 3.6 or higher
• Pip (Python package installer)

Installation

First, clone the repository:

git clone https://github.com/BAXTOR95/pdf-to-speech.git
cd pdf-to-speech

Then, install the required Python libraries:

pip install -r requirements.txt

Usage

Basic Conversion

Convert all PDFs in the input_files directory to MP3 audio files:

python main.py --all

Interactive Mode

Selectively convert PDFs by choosing them interactively:

python main.py --interactive

Resume Processing

Resume a previous processing session, skipping already processed files:

python main.py --resume

Convert Specific Files

Convert specific PDF files:

python main.py file1.pdf file2.pdf file3.pdf

Segment by Chapters

Convert PDFs and segment them by chapters:

python main.py --all --segment-by-chapter

Specify Output Format

Convert PDFs to a specific audio format (MP3, WAV, or OGG):

python main.py --all -f wav

Set Metadata

Specify title and author metadata for the audio files:

python main.py --all --title "Example Title" --author "Author Name"

Set Language

Override automatic language detection:

python main.py --all --language en

Directory Structure

• input_files/: Place your PDFs here before processing.
• output_files/: Audio files are saved in this directory after processing.
• progress.txt: Tracks the progress of processed files (used with --resume).

Modules and Functions

• pdf_reader.py: Contains functions to extract text and metadata from PDFs.
• text_to_speech.py: Handles the conversion of text to speech using Google TTS.
• main.py: The main script to run conversions, handling command-line arguments and processing logic.

Customization

You can modify the script to suit your needs:

• Change the chapter_pattern in pdf_reader.py to match different chapter styles.
• Adjust the TTS properties in text_to_speech.py for different voices or speeds.

Troubleshooting

• Missing PDFs: Ensure all PDFs are in the input_files directory.
• Permission Issues: Make sure you have read and write permissions for the directories.
• Dependency Errors: Run pip install -r requirements.txt to ensure all dependencies are installed.

Contributing

Feel free to fork the repository, make your changes, and create a pull request with your improvements.

Authors

• Brian Arriaga - Initial work - BAXTOR95