Listen to Your PDFs: A Python Guide to Converting Documents into Audio

Introduction

In an increasingly digital world, the demand for accessible content continues to grow. One powerful way to enhance accessibility is by converting PDF documents into audio format for easy access and comprehension anywhere. This can enhance productivity, portability, reduce working hours and enable multitasking for busy individuals.

In this article, we will look at in detail the steps we can take to harness the power of the popular Python programming language to seamlessly convert PDFs to audio using 2 powerful Python libraries.

Let’s dive in and unleash our superpowers as we learn to convert PDFs to audio using Python.

Understanding The PDF File Format

Originally developed by Adobe Systems in the early 1990s, the Portable Document Format (PDF) has become one of the most widely used file formats for sharing and preserving documents consistently and securely; it provides a reliable and flexible solution for sharing and preserving electronic documents while maintaining their visual integrity and security. It's widespread adoption and extensive features make it an indispensable format in today's digital world.

PDFs consist of a well-defined structure and various components that work together to store and display the document's content accurately. Understanding the structure and components of a PDF file helps in manipulating and extracting information from it. There are several components of a basic PDF file including; the Header, Body, Cross-Reference, Trailer, Catalog, Pages, Fonts, Images, Annotations, and Metadata.

For this article anyways, we will mostly be using the Body and Pages components of a PDF;

• Body: Contains objects and streams that define the document's content, such as text, images, fonts, annotations, and forms.
• Pages: Represent the visual content and structure of the document.

Challenges in extracting text from PDFs

To convert PDFs to audio using Python, we need to find a way to extract the text in the document body pages before processing it to audio.

However, extracting text from PDFs can present several challenges due to the diverse structure and nature of these documents, which mainly results from the complexity of the method of creation. Below are common challenges faced in extracting text from PDFs;

• Scanned Documents: PDFs created from scanned images, do not contain selectable text, which makes text extraction a little tricky, requiring some form of optical character recognition (OCR) techniques to extract the text accurately.
• Complex Layouts: PDFs with complex/several tables, columns or graphics makes text extraction a little bit harder.
• Watermarks and Annotations: The presence of watermarks overlayed on the text of PDFs will require extra filtering and processing to accurately extract text from such documents.
• Text Encoding: PDFs can use various text encodings, including standard encodings, custom encodings, or even subsetted fonts. Dealing with different encodings and character mappings can lead to incorrect or garbled text extraction.
• Encrypted or Password-Protected PDFs: Text extraction from password-protected or encrypted PDFs can be difficult without the correct credentials or decryption mechanisms.

Addressing these challenges often involves using specialized libraries or tools that support OCR, handle various text encodings, handle complex layouts, and provide mechanisms to handle encryption or password protection.

Prerequisites

Before diving into this article, it is beneficial to have these technologies installed and a basic understanding of the following concepts:

• Have a working knowledge of the Python programming language.
• Have Python V3.10+ installed

In addition to the above listed, we will need an actual PDF document to convert to audio, so we will be using Categories of Programming Languages study material on the categories of programming languages.

Required Python Libraries

To enable us to convert from PDF to audio we will be working with 2 main libraries;

• PyPDF2
• Pyttsx3

According to the official PyPDF2 documentation, PyPDF2 is described as;

“a free and open-source pure-python PDF library capable of splitting, merging, cropping, and transforming the pages of PDF files. It can also add custom data, viewing options, and passwords to PDF files. PyPDF2 can retrieve text and metadata from PDFs as well”

To install PyPDF2, run the command below

pip install PyPDF2

Pyttsx on the other hand is also an open source free python library for converting pure text to audio, it offers a range of features, including increasing the playback speed, changing the voice of the speaker, increasing the playback volume, and many other useful functionalities. It works well without the need for an internet connection.

We can now go ahead and install pyttsx3

pip install pyttsx3

In the case of PDFs with scanned images or other complexities, other libraries such as pytesseract, or pdf2image can be used in conjunction with PyPDF2 to perform OCR on scanned PDFs.

Converting Our PDF to Audio

Our PDF Categories of Programming Languages contains 14 pages, which we can read through all, but for this article, we will loop through pages 1 - 6 to extract the text and then convert it to audio.

We first import the 2 installed packages, PyPDF2 and Pyttsx3.

import PyPDF2
import pyttsx3

After which we open the PDF file we are working with using the open function;

import PyPDF2
import pyttsx3

book = open(r'COPL.pdf', 'rb')

With that, we can now create an empty “text” variable to store the text we will be extracting from the pages we will be working with.

import PyPDF2
import pyttsx3

book = open(r'COPL.pdf', 'rb')
text = ""

We can then create a PdfReader object named "pdfreader" using the PyPDF2 library. PdfReader is a class provided by PyPDF2 that allows reading and extracting information from PDF files.

At the same time, we can initialize the text-to-speech (TTS) engine using the pyttsx3 library;

import PyPDF2
import pyttsx3

book = open(r'COPL.pdf', 'rb')
text = ""
pdfreader = PyPDF2.PdfReader(book)
speaker= pyttsx3.init()

With this, we can now create a for loop that iterates through pages 1 - 6 of our PDF documents, then extract and add the text from each of those pages to the “text” variable we created earlier.

import PyPDF2
import pyttsx3

book = open(r'COPL.pdf', 'rb')
text = ""
pdfreader = PyPDF2.PdfReader(book)
speaker= pyttsx3.init()

for page in range(0,5):
    CurrentPage = pdfreader.pages[page]
    text += CurrentPage.extract_text()

With all these in place, we just need to pass in the text extracted to the “say” function of the speaker instance, then call the "runAndWait" function to listen to our PDF speak to us.

import PyPDF2
import pyttsx3

book = open(r'PL.pdf', 'rb')
text = ""
pdfreader = PyPDF2.PdfReader(book)
speaker= pyttsx3.init()

for page in range(0,5):
    CurrentPage = pdfreader.pages[page]
    text += CurrentPage.extract_text()
    speaker.say(text)
    speaker.runAndWait()

Conclusion

As you have seen, by utilizing Python libraries such as PyPDF2 and pyttsx3, users can easily automate the process of converting PDFs to audio and enhance accessibility for individuals with visual impairments or auditory learning preferences. Through this technology, we can foster inclusivity and make information universally accessible.

Converting PDFs to audio with Python is straightforward and quite simple thanks to PyPDF2 and Pyttsx3. You can visit their official documentation pages to extend your knowledge about them and explore more functionalities.