Categories: BlogPython Tutorials

How to Develop a PDF-to-Audio Converter with Python

Python PDF to Speech Web App - Build a simple Flask application to convert PDF files to audio.

Introduction – PDF-to-Audio Converter

Have you ever found yourself wanting to listen to the content of a PDF instead of reading it? Whether you’re busy, multitasking, or simply prefer audio formats, Well, you’re in luck! In this blog post, we will guide you through creating a PDF-to-Audio converter using Python. This tool will take a PDF file, extract its text, convert the text into audio, and save it as an MP3 file.

We’ll be using some powerful Python libraries to accomplish this task: PyMuPDF for reading PDF files, Google Text-to-Speech (gTTS) for converting text to speech, and Flask for creating a simple web interface. Let’s start! Before we begin coding, let’s observe how our PDF-to-Audio Converter Application works

Watch our Python tutorial on developing a PDF-to-Audio Converter! Learn how to automate PDF to speech conversion using PyMuPDF and gTTS. Convert PDFs to MP3 effortlessly with our step-by-step guide.

Prerequisites

Before we start coding, make sure you have Python installed on your computer. You can download Python from python.org. We will also need to install a few Python libraries. Open your terminal and run the following commands:

pip install Flask
pip install PyMuPDF
pip install gTTS

These commands will install Flask, PyMuPDF, and Google Text-to-Speech (gTTS).

Text-to-Speech Python Tutorial – Step-by-step tutorial on developing a PDF to audio converter script in Python.

Setting Up the Project of PDF-to-Audio Converter

First, let’s create a project directory. Open your terminal and run:

mkdir pdf_to_audio
cd pdf_to_audio

Inside this directory, we will create the necessary files for our project:

  • app.py: This will contain our Flask application.
  • templates/index.html: This will be our HTML file for the web interface.
  • static/style.css: This will contain our CSS styles.

Let’s start by creating these files.

Creating the Flask Application for PDF-to-Audio Converter

app.py

Open your text editor or IDE and create a new file named app.py. This file will contain our Flask application.

First, let’s import the necessary modules and set up our Flask app:

from flask import Flask, render_template, request, send_file, jsonify
import os
import fitz  # PyMuPDF
from gtts import gTTS  # Google Text-to-Speech
from concurrent.futures import ThreadPoolExecutor
import threading

app = Flask(__name__)
app.secret_key = (Your Secret Key)  # Replace with your own secret key

Flask Import and Setup

  • from flask import Flask, render_template, request, send_file, jsonify: This line imports necessary modules from Flask, which is a Python web framework. These modules help manage web requests, display templates, send files, and convert Python data into JSON format for responses.
Create a PDF to Audio Converter in Python – Turn PDF text into speech with our comprehensive Python guide.

Operating System (os) Import

  • import os: This module provides functions for interacting with the operating system. We used here to perform operations related to files and directories.

PyMuPDF (fitz) Import

  • import fitz: This is a Python library (PyMuPDF) used for reading PDF files and extracting text from them.

Google Text-to-Speech (gTTS) Import

ThreadPoolExecutor and Threading Import

  • from concurrent.futures import ThreadPoolExecutor: This module provides a high-level interface for asynchronously executing functions using threads or processes.
  • import threading: Threading is Python’s way of achieving concurrency, allowing multiple tasks to run concurrently.

Flask App Setup

  • app = Flask(__name__): Creates a new Flask application instance.
  • app.secret_key = (Your Secret Key): Replace this with your own secret key. This line sets a secret key for the Flask application. The secret key is used to secure session data and other cryptographic operations within Flask. It should be kept private and secure.

So far,

  • We’re setting up a web application using Flask.
  • We import modules that help us handle web requests, work with PDFs, convert text to speech, and manage concurrent tasks.
  • The secret key ensures that session data remains secure and encrypted within our web application.

Status Tracking for PDF-to-Audio converter

We will keep track of the conversion status using a shared dictionary. We’ll use a lock to ensure thread-safe updates to this dictionary:

status = {
    "current_chunk": 0,
    "total_chunks": 0,
    "status": "idle"
}

status_lock = threading.Lock()

def update_status(current, total, state):
    with status_lock:
        status["current_chunk"] = current
        status["total_chunks"] = total
        status["status"] = state

Shared Status Dictionary

  • status = { "current_chunk": 0, "total_chunks": 0, "status": "idle" }
  • Here, status is a dictionary that stores information about the current state of a conversion process.
  • current_chunk: Tracks the number of the current chunk (part) of the PDF being processed.
  • total_chunks: Indicates the total number of chunks (parts) in the PDF that need to be processed.
  • status: Describes the current status of the conversion process, which starts as “idle”.

Thread Lock for Synchronization

  • status_lock = threading.Lock(): This line creates a Lock object named status_lock.
  • A Lock in Python ensures that only one thread can access a shared resource (in this case, the status dictionary) at a time.
  • This prevents conflicts and ensures that updates to the status dictionary are handled safely when multiple threads are involved.

Update Status Function

def update_status(current, total, state):

  • This function update_status takes three parameters:
    • current: The current chunk number being processed.
    • total: The total number of chunks in the PDF.
    • state: The current state of the conversion process (e.g., “processing”, “completed”, “error”).

with status_lock

  • Using with status_lock: ensures that the code block inside it is executed while holding the status_lock. This prevents other threads from modifying status concurrently.

Inside the with block

  • status["current_chunk"] = current: Updates the current_chunk in the status dictionary with the provided current value.
  • status["total_chunks"] = total: Updates the total_chunks in the status dictionary with the provided total value.
  • status["status"] = state: Updates the status in the status dictionary with the provided state value, indicating the current state of the conversion process.

In simpler terms:

  • We use a dictionary named status to keep track of where we are in converting a PDF to audio.
  • The status_lock ensures that only one part of the program can update this dictionary at a time, preventing mix-ups.
  • The update_status function makes it easy to tell what part of the PDF we’re on and if the conversion is done or still going.

PDF to Text Conversion – PDF-to-Audio Converter

Next, we need a function to convert the PDF to text. We will use PyMuPDF for this:

def pdf_to_text(pdf_file):
    text = ""
    try:
        doc = fitz.open(pdf_file)
        for page_num in range(len(doc)):
            page = doc.load_page(page_num)
            text += page.get_text()
        doc.close()
    except Exception as e:
        print(f"Error reading PDF: {e}")
        return None
    return text

Function Definition

def pdf_to_text(pdf_file):
  • This line defines a function named pdf_to_text that takes pdf_file as a parameter. This parameter is expected to be the path to a PDF file.

Initialization of text Variable

text = ""
  • text is initialized as an empty string. This variable will accumulate all the text content extracted from the PDF.

Opening and Reading the PDF File – PDF-to-Audio Converter

try:
    doc = fitz.open(pdf_file)
    for page_num in range(len(doc)):
        page = doc.load_page(page_num)
        text += page.get_text()
    doc.close()
except Exception as e:
    print(f"Error reading PDF: {e}")
    return None

fitz.open(pdf_file): Opens the PDF file specified by pdf_file using PyMuPDF (also known as fitz).

for page_num in range(len(doc)): Iterates through each page in the PDF.

  • page = doc.load_page(page_num): Loads the current page from the PDF.
  • text += page.get_text(): Retrieves the text content of the current page and appends it to the text variable.

doc.close(): Closes the PDF document after all pages have been processed.

except Exception as e: Handles any exceptions that may occur during the PDF reading process.

  • If an error occurs (Exception), it prints an error message indicating the issue (f"Error reading PDF: {e}").
  • It then returns None to indicate that the function did not successfully extract text from the PDF.

In summarry,

  • The pdf_to_text function reads a PDF file (pdf_file) and extracts its text content.
  • It uses PyMuPDF (fitz) to open the PDF and iterate through each page to get the text.
  • If there’s an error during the reading process, it prints an error message and returns None.
  • Otherwise, it returns all the text extracted from the PDF as a single string.

Returning Extracted Text

return text
  • If the PDF is read successfully without any exceptions, the function returns the accumulated text extracted from all pages of the PDF.

Text to MP3 Conversion

We also need a function to convert text to MP3. We will use Google Text-to-Speech (gTTS) for this:

def text_to_mp3_chunk(chunk, chunk_index, output_directory):
    try:
        tts = gTTS(text=chunk, lang='en')
        temp_chunk_path = os.path.join(output_directory, f'chunk_{chunk_index}.mp3')
        tts.save(temp_chunk_path)
        print(f"Saved chunk {chunk_index} to {temp_chunk_path}")
    except Exception as e:
        print(f"Error converting chunk {chunk_index} to MP3: {e}")

Here’s a simplified explanation of the Python function text_to_mp3_chunk that uses Google Text-to-Speech (gTTS) to convert a chunk of text into an MP3 file:

Function Definition

def text_to_mp3_chunk(chunk, chunk_index, output_directory):

This line defines a function named text_to_mp3_chunk that takes three parameters:

  • chunk: The text content to be converted into speech.
  • chunk_index: The index or identifier of the current chunk.
  • output_directory: The directory where the MP3 file will be saved.

Text-to-Speech Conversion – PDF-to-Audio Converter

Text Extraction with PyMuPDF – Learn how to extract text from PDFs using Python’s PyMuPDF for audio conversion.
try:
    tts = gTTS(text=chunk, lang='en')
    temp_chunk_path = os.path.join(output_directory, f'chunk_{chunk_index}.mp3')
    tts.save(temp_chunk_path)
    print(f"Saved chunk {chunk_index} to {temp_chunk_path}")
  • gTTS(text=chunk, lang='en'): Creates a gTTS (Google Text-to-Speech) object with the specified chunk of text and language (‘en’ for English).
  • temp_chunk_path = os.path.join(output_directory, f'chunk_{chunk_index}.mp3'): Constructs the path where the MP3 file will be saved. The file name includes chunk_index to differentiate between different chunks.
  • tts.save(temp_chunk_path): Saves the synthesized speech as an MP3 file at temp_chunk_path.print(f"Saved chunk {chunk_index} to {temp_chunk_path}"):
  • Prints a message confirming the successful saving of the MP3 file.

Error Handling

except Exception as e:
    print(f"Error converting chunk {chunk_index} to MP3: {e}")
  • If an error occurs during the text-to-speech conversion process (Exception), it prints an error message indicating the issue (f"Error converting chunk {chunk_index} to MP3: {e}").

In simpler terms:

  • The text_to_mp3_chunk function converts a piece of text (chunk) into spoken audio using Google Text-to-Speech.
  • It saves the synthesized speech as an MP3 file in the specified output_directory.
  • If successful, it prints a confirmation message with the file path.
  • If there’s an error during the conversion process, it prints an error message describing the issue

Combining MP3 Chunks

To handle large texts, we will split the text into chunks, convert each chunk to MP3, and then combine these chunks into a single MP3 file:

def combine_mp3_chunks(chunk_count, output_directory, final_mp3_path):
    try:
        with open(final_mp3_path, 'wb') as final_mp3_file:
            for i in range(chunk_count):
                chunk_path = os.path.join(output_directory, f'chunk_{i}.mp3')
                with open(chunk_path, 'rb') as chunk_file:
                    final_mp3_file.write(chunk_file.read())
                os.remove(chunk_path)  # Clean up chunk file
        print(f"MP3 saved to {final_mp3_path}")
    except Exception as e:
        print(f"Error combining MP3 chunks: {e}")

Function Definition

def combine_mp3_chunks(chunk_count, output_directory, final_mp3_path):

This line defines a function named combine_mp3_chunks that takes three parameters:

  • chunk_count: The total number of MP3 chunks to combine.
  • output_directory: The directory where the MP3 chunks are stored.
  • final_mp3_path: The path where the final combined MP3 file will be saved.

Combining MP3 Chunks

try:
    with open(final_mp3_path, 'wb') as final_mp3_file:
        for i in range(chunk_count):
            chunk_path = os.path.join(output_directory, f'chunk_{i}.mp3')
            with open(chunk_path, 'rb') as chunk_file:
                final_mp3_file.write(chunk_file.read())
            os.remove(chunk_path)  # Clean up chunk file
    print(f"MP3 saved to {final_mp3_path}")
  • with open(final_mp3_path, 'wb') as final_mp3_file:: Opens final_mp3_path in write mode ('wb'), creating a new file for the final combined MP3.for i in range(chunk_count):: Iterates through each chunk index from 0 to chunk_count - 1.
  • chunk_path = os.path.join(output_directory, f'chunk_{i}.mp3'): Constructs the path to each MP3 chunk file.
  • with open(chunk_path, 'rb') as chunk_file:: Opens chunk_path in read mode ('rb') to read its content.
  • os.remove(chunk_path): Deletes (removes) the current chunk file (chunk_path) after its content has been written to the final MP3 file to clean up disk space.

Error Handling

except Exception as e:
    print(f"Error combining MP3 chunks: {e}")
  • If an error occurs during the combination process (Exception), it prints an error message describing the issue (f"Error combining MP3 chunks: {e}").

Let’s summarize this

  • The combine_mp3_chunks function takes multiple MP3 chunks stored in output_directory, combines them into a single MP3 file (final_mp3_path), and deletes the individual chunk files afterward.
  • It opens each chunk file, reads its content, writes it to the final MP3 file, and then removes the chunk file.
  • If there’s an error during the process, it prints an error message explaining what went wrong.

Flask Routes

Now, let’s set up the routes for our Flask application:

  • The home route (/) will display the form to upload the PDF file.
  • The /status route will return the current status of the conversion.
  • The /download/<filename> route will handle the download of the MP3 file.
@app.route('/', methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        pdf_file = request.files['pdf_file']
        if pdf_file.filename == '':
            return "No file chosen"

        mp3_output_directory = './uploads'
        if not os.path.exists(mp3_output_directory):
            os.makedirs(mp3_output_directory)

        if pdf_file and pdf_file.filename.endswith('.pdf'):
            try:
                # Save the uploaded PDF file
                pdf_path = os.path.join(mp3_output_directory, pdf_file.filename)
                pdf_file.save(pdf_path)
                print(f"PDF saved to {pdf_path}")

                # Convert PDF to text
                text = pdf_to_text(pdf_path)
                if text:
                    print(f"Extracted text: {text[:500]}...")  # Print first 500 characters for verification

                    # Convert text to MP3
                    mp3_filename = f"{os.path.splitext(os.path.basename(pdf_path))[0]}.mp3"
                    mp3_path = os.path.join(mp3_output_directory, mp3_filename)
                    print(f"Converting text to MP3 and saving to {mp3_path}...")

                    # Splitting the text into chunks
                    text_chunks = [text[i:i + 1000] for i in range(0, len(text), 1000)]
                    update_status(0, len(text_chunks), 'processing')

                    # Process chunks in parallel using ThreadPoolExecutor
                    with ThreadPoolExecutor() as executor:
                        futures = [executor.submit(text_to_mp3_chunk, chunk, i, mp3_output_directory) for i, chunk in enumerate(text_chunks)]
                        for i, future in enumerate(futures):
                            future.result()  # Ensure each thread completes
                            update_status(i + 1, len(text_chunks), 'processing')

                    # Combine all chunks into a single MP3 file
                    combine_mp3_chunks(len(text_chunks), mp3_output_directory, mp3_path)
                    update_status(len(text_chunks), len(text_chunks), 'done')

                    return jsonify({"status": "done", "download_url": f"/download/{mp3_filename}"})
                else:
                    print("Error converting PDF to text.")
                    return "Error converting PDF to text. Please try again."
            except Exception as e:
                print(f"Error processing PDF: {e}")
                return "Error processing PDF. Please try again."

    return render_template('index.html')

@app.route('/status', methods=['GET'])
def get_status():
    with status_lock:
        return jsonify(status)

@app.route('/download/<filename>')
def download(filename):
    mp3_file_path = os.path.join('./uploads', filename)
    try:
        print(f"Attempting to send file: {mp3_file_path}")
        return send_file(mp3_file_path, as_attachment=True)
    except Exception as e:
        print(f"Error sending file: {e}")
        return "Error sending file. Please try again."

if __name__ == '__main__':
    app.run(debug=True)

Index Route (/)

This route handles both GET and POST requests.On POST request:

  • It checks if a PDF file is uploaded (pdf_file).
  • Saves the PDF file to ./uploads directory.
  • Converts the PDF to text using pdf_to_text.
  • Splits the text into chunks and converts each chunk to MP3 using text_to_mp3_chunk.
  • Combines all MP3 chunks into a single MP3 file using combine_mp3_chunks.
  • Updates conversion status using update_status.
  • Returns JSON response with conversion status and download URL for the MP3.

On GET request or if no file is uploaded, it renders an index.html template for file upload.

Status Route (/status)

@app.route('/status', methods=['GET'])
def get_status():
    with status_lock:
        return jsonify(status)
  • This route handles GET requests to /status.
  • It uses status_lock to ensure thread-safe access to status dictionary.
  • Returns JSON response containing the current conversion status (status dictionary).

Download Route (/download/<filename>)

@app.route('/download/<filename>')
def download(filename):
    mp3_file_path = os.path.join('./uploads', filename)
    try:
        print(f"Attempting to send file: {mp3_file_path}")
        return send_file(mp3_file_path, as_attachment=True)
    except Exception as e:
        print(f"Error sending file: {e}")
        return "Error sending file. Please try again."
  • This route handles requests to download the MP3 file identified by <filename>.
  • Constructs the file path (mp3_file_path) using filename from ./uploads directory.
  • Attempts to send the file (mp3_file_path) as an attachment for download using send_file.
  • Handles exceptions and prints errors if file sending fails.

Main Execution (__name__ == '__main__') and Debug Mode

if __name__ == '__main__':
    app.run(debug=True)
  • This block ensures that the Flask application (app) runs when this script is executed directly.
  • debug=True enables debug mode in Flask, providing detailed error messages and auto-reloading the server when code changes.

In simpler terms:

  • The Flask application provides routes (/, /status, /download/<filename>) for uploading a PDF, checking conversion status, and downloading the converted MP3.
  • It handles file uploads, converts PDF to text, splits text into manageable chunks, converts each chunk to MP3, combines MP3 chunks into a single file, and updates status accordingly.
  • Error handling ensures that any issues during these processes are logged, and appropriate messages are returned to users.

Creating the HTML Template for PDF-to-Audio Converter

Next, we need to create the HTML template for our web interface.

templates/index.html

Create a directory named templates in your project directory, and inside it, create a file named index.html. This file will contain the HTML for our web interface:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>PDF to MP3 Converter</title>
    <link rel="stylesheet" href="/static/style.css">
    <script src="https://code.jquery.com/jquery-3.6.0.min.js"></script>
</head>
<body>
    <h1>PDF to MP3 Converter</h1>
    <form id="uploadForm" enctype="multipart/form-data">
        <input type="file" name="pdf_file" id="pdf_file" accept="application/pdf">
        <button type="submit">Upload and Convert</button>
    </form>
    <div id="status" style="display:none;">
        <p id="progress">Converting...</p>
        <progress id="progressBar" value="0" max="100"></progress>
    </div>
    <div id="downloadLink" style="display:none;">
        <a id="downloadAnchor" href="" target="_blank">Download Audio</a>
    </div>

    <script>
        $(document).ready(function(){
            $('#uploadForm').submit(function(event){
                event.preventDefault();

                var formData = new FormData(this);
                $('#status').show();
                $('#progress').text('Uploading PDF...');
                $('#progressBar').val(0);

                $.ajax({
                    url: '/',
                    type: 'POST',
                    data: formData,
                    processData: false,
                    contentType: false,
                    success: function(data){
                        if(data.status === 'done'){
                            $('#progress').text('Conversion complete!');
                            $('#progressBar').val(100);
                            $('#downloadAnchor').attr('href', data.download_url);
                            $('#downloadLink').show();
                        } else {
                            $('#progress').text('Converting PDF to MP3...');
                            checkStatus();
                        }
                    },
                    error: function(){
                        alert('Error uploading file.');
                    }
                });
            });

            function checkStatus() {
                $.ajax({
                    url: '/status',
                    type: 'GET',
                    success: function(data){
                        if(data.status === 'processing'){
                            $('#progress').text('Processing chunk ' + data.current_chunk + ' of ' + data.total_chunks);
                            $('#progressBar').val((data.current_chunk / data.total_chunks) * 100);
                            setTimeout(checkStatus, 1000);
                        } else if(data.status === 'done'){
                            $('#progress').text('Conversion complete!');
                            $('#progressBar').val(100);
                            $('#downloadAnchor').attr('href', data.download_url);
                            $('#downloadLink').show();
                        }
                    },
                    error: function(){
                        alert('Error checking status.');
                    }
                });
            }
        });
    </script>
</body>
</html>

Adding CSS Styles

Create a directory named static in your project directory, and inside it, create a file named style.css. This file will contain our CSS styles:

static/style.css

body {
    font-family: Arial, sans-serif;
    text-align: center;
    margin-top: 50px;
}

form {
    margin-bottom: 20px;
}

#status {
    margin-top: 20px;
}

#downloadLink {
    margin-top: 20px;
}

Running the Application of PDF-to-Audio Converter

Python PDF to Speech Web App – Build a simple Flask application to convert PDF files to audio.

Now that we have all the necessary files, let’s run our Flask application. In your terminal, navigate to your project directory and run:

python app.py

Open your web browser and go to http://127.0.0.1:5000/. You should see the web interface for uploading a PDF file.

Uploading and Converting a PDF

  1. Select a PDF File: Click on the “Choose File” button and select a PDF file from your computer.
  2. Upload and Convert: Click on the “Upload and Convert” button to start the conversion process.
  3. View Progress: The progress bar and status messages will update to show the conversion progress.
  4. Download the MP3: Once the conversion is complete, a download link will appear. Click on the link to download the MP3 file.

Conclusion

Congratulations! You have successfully created a PDF-to-Audio converter using Python. This project demonstrates how to integrate various Python libraries to build a useful tool. By combining Flask for the web interface, PyMuPDF for reading PDFs, and gTTS for text-to-speech conversion, we created a perfect user experience for converting PDF files to MP3.

Feel free to expand this project by adding features like language selection for the text-to-speech conversion or supporting more file formats.

Source Code for PDF-to-Audio Converter

As I have already provided the complete index.html and styles.css files, here is the full app.py file.

app.py

from flask import Flask, render_template, request, send_file, jsonify
import os
import fitz  # PyMuPDF
from gtts import gTTS  # Google Text-to-Speech
from concurrent.futures import ThreadPoolExecutor
import threading

app = Flask(__name__)
app.secret_key = (Your Secret Key) # Replace this with your own secret key

status = {
    "current_chunk": 0,
    "total_chunks": 0,
    "status": "idle"
}

# Lock for thread-safe status updates
status_lock = threading.Lock()

# Function to convert PDF to text using PyMuPDF (fitz)
def pdf_to_text(pdf_file):
    text = ""
    try:
        doc = fitz.open(pdf_file)
        for page_num in range(len(doc)):
            page = doc.load_page(page_num)
            text += page.get_text()
        doc.close()
    except Exception as e:
        print(f"Error reading PDF: {e}")
        return None
    return text

# Function to convert a chunk of text to MP3 using Google Text-to-Speech (gTTS)
def text_to_mp3_chunk(chunk, chunk_index, output_directory):
    try:
        tts = gTTS(text=chunk, lang='en')
        temp_chunk_path = os.path.join(output_directory, f'chunk_{chunk_index}.mp3')
        tts.save(temp_chunk_path)
        print(f"Saved chunk {chunk_index} to {temp_chunk_path}")
    except Exception as e:
        print(f"Error converting chunk {chunk_index} to MP3: {e}")

# Function to combine multiple MP3 chunks into a single MP3 file
def combine_mp3_chunks(chunk_count, output_directory, final_mp3_path):
    try:
        with open(final_mp3_path, 'wb') as final_mp3_file:
            for i in range(chunk_count):
                chunk_path = os.path.join(output_directory, f'chunk_{i}.mp3')
                with open(chunk_path, 'rb') as chunk_file:
                    final_mp3_file.write(chunk_file.read())
                os.remove(chunk_path)  # Clean up chunk file
        print(f"MP3 saved to {final_mp3_path}")
    except Exception as e:
        print(f"Error combining MP3 chunks: {e}")

def update_status(current, total, state):
    with status_lock:
        status["current_chunk"] = current
        status["total_chunks"] = total
        status["status"] = state

# Route for the home page
@app.route('/', methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        pdf_file = request.files['pdf_file']
        if pdf_file.filename == '':
            return "No file chosen"

        mp3_output_directory = './uploads'
        if not os.path.exists(mp3_output_directory):
            os.makedirs(mp3_output_directory)

        if pdf_file and pdf_file.filename.endswith('.pdf'):
            try:
                # Save the uploaded PDF file
                pdf_path = os.path.join(mp3_output_directory, pdf_file.filename)
                pdf_file.save(pdf_path)
                print(f"PDF saved to {pdf_path}")

                # Convert PDF to text
                text = pdf_to_text(pdf_path)
                if text:
                    print(f"Extracted text: {text[:500]}...")  # Print first 500 characters for verification

                    # Convert text to MP3
                    mp3_filename = f"{os.path.splitext(os.path.basename(pdf_path))[0]}.mp3"
                    mp3_path = os.path.join(mp3_output_directory, mp3_filename)
                    print(f"Converting text to MP3 and saving to {mp3_path}...")

                    # Splitting the text into chunks
                    text_chunks = [text[i:i + 1000] for i in range(0, len(text), 1000)]
                    update_status(0, len(text_chunks), 'processing')

                    # Process chunks in parallel using ThreadPoolExecutor
                    with ThreadPoolExecutor() as executor:
                        futures = [executor.submit(text_to_mp3_chunk, chunk, i, mp3_output_directory) for i, chunk in enumerate(text_chunks)]
                        for i, future in enumerate(futures):
                            future.result()  # Ensure each thread completes
                            update_status(i + 1, len(text_chunks), 'processing')

                    # Combine all chunks into a single MP3 file
                    combine_mp3_chunks(len(text_chunks), mp3_output_directory, mp3_path)
                    update_status(len(text_chunks), len(text_chunks), 'done')

                    return jsonify({"status": "done", "download_url": f"/download/{mp3_filename}"})
                else:
                    print("Error converting PDF to text.")
                    return "Error converting PDF to text. Please try again."
            except Exception as e:
                print(f"Error processing PDF: {e}")
                return "Error processing PDF. Please try again."

    return render_template('index.html')

# Route to get the current status
@app.route('/status', methods=['GET'])
def get_status():
    with status_lock:
        return jsonify(status)

# Route to download the generated MP3 file
@app.route('/download/<filename>')
def download(filename):
    mp3_file_path = os.path.join('./uploads', filename)
    try:
        print(f"Attempting to send file: {mp3_file_path}")
        return send_file(mp3_file_path, as_attachment=True)
    except Exception as e:
        print(f"Error sending file: {e}")
        return "Error sending file. Please try again."

if __name__ == '__main__':
    app.run(debug=True)

External Resources on PDF-to-Audio Converter

Frequently Asked Questions – PDF-to-Audio Converter

FAQ Section
1. What is the purpose of a PDF-to-Audio Converter?
A PDF-to-Audio Converter allows users to convert text from PDF documents into audio files. This is particularly useful for those who prefer listening to content rather than reading, such as during commutes or for accessibility reasons for visually impaired individuals.
2. What programming languages and libraries are used in this project?
The project is primarily developed using Python. Key libraries used include: Flask for creating the web application. PyMuPDF (Fitz) for extracting text from PDF files. gTTS (Google Text-to-Speech) for converting text to audio. ThreadPoolExecutor from the concurrent.futures module for handling parallel processing.
3. How do I install the necessary libraries for this project?
You can install the required libraries using pip, the Python package installer. Here are the commands to install Flask, PyMuPDF, and gTTS: 

pip install Flask
pip install PyMuPDF
pip install gTTS
4. Can I customize the language or voice used for the audio conversion?
Yes, you can customize the language by changing the lang parameter in the gTTS function. However, the Google Text-to-Speech library (gTTS) primarily offers different languages but not multiple voice options. For more advanced voice options, you might consider using other text-to-speech services like Amazon Polly or IBM Watson Text-to-Speech.
5. How can I handle large PDF files with this converter?
The converter processes large PDF files by splitting the extracted text into smaller chunks and converting each chunk separately. This ensures that the conversion process is manageable and efficient. The ThreadPoolExecutor is used to handle these chunks in parallel, speeding up the overall process.
6. Where are the generated audio files stored, and how can I download them?
The generated audio files are stored in the uploads directory within the project folder. Once the conversion is complete, a download link is provided on the web page, allowing you to download the audio file directly to your local device.
Emmimal Alexander

Emmimal Alexander is an AI educator and the author of Neural Networks and Deep Learning with Python. She is the founder of EmiTechLogic, where she focuses on explaining how modern AI systems are built, trained, and deployed — and why they fail in real-world settings. Her work centers on neural networks, large language models, AI hallucination, and production engineering constraints, with an emphasis on understanding the architectural trade-offs behind modern AI. She is known for translating complex theoretical foundations into practical engineering insights grounded in real system behavior.

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2 years ago

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