Convert PDFs to Audiobooks with AI

Convert PDFs to Audiobooks with AI

Table of Contents:

1. Introduction
2. The Challenge of Reading Research Papers on Walks
3. Kaz Sato's Project: Transforming PDFs into Audiobooks
4. Building Your Own Audiobook Conversion Project 4.1 Setting Up a Google Cloud Storage Bucket 4.2 Extracting Text from PDFs using the Vision API 4.3 Implementing the Audiobook-Making Pipeline
5. Customizing the Audiobook Text 5.1 Removing Garbage Text with Auto ML Tables 5.2 Training the Custom Machine-Learning Model 5.3 Finding the Body Text in PDFs
6. Generating Computer Voices with Google Cloud Text-to-Speech 6.1 Choosing a Voice for the Audiobook 6.2 Updating the Code for Automated Audiobook Generation
7. Listening to the Audiobook
8. Conclusion

Building Your Own Audiobook Conversion Project

In this article, we will explore the challenge of reading research papers while going for walks and how machine learning can help solve this problem. We'll dive into Kaz Sato's project, which involves transforming PDFs into audiobooks, and learn how to build our own version of this project. By using computer vision and text-to-speech technologies, we'll be able to convert PDFs into spoken words and enjoy research papers on the go.

Introduction

When we find ourselves in quarantine, exploring new hobbies becomes essential. One such hobby that has gained popularity is going for walks. Whether it's for exercise or relaxation, walks have become a daily routine for many. However, reading research papers can be challenging during walks, until now. Thanks to a new project developed by my colleague, Kaz Sato, we can now transform PDFs into audiobooks using machine learning. In this article, I'll guide You on how to use computer vision and text-to-speech to convert your own PDFs into audiobooks, allowing you to enjoy research papers with ease while strolling around.

The Challenge of Reading Research Papers on Walks

While going for walks, engaging in activities like listening to podcasts or taking meetings is easy. However, reading research papers poses a unique challenge. Holding a physical paper or even trying to read a PDF on a smartphone can be inconvenient and disrupt the walking experience. As an avid reader, I faced this challenge until I learned about Kaz Sato's project. By using machine learning techniques, Kaz was able to convert PDFs into audiobooks, making research papers accessible and enjoyable during walks.

Kaz Sato's Project: Transforming PDFs into Audiobooks

Kaz Sato, Based in Japan, developed an innovative project that uses machine learning to transform PDFs into audiobooks. He utilized the Vision API's OCR feature to extract text from PDFs and then used the Text-to-Speech API to convert the pre-processed text into audio files. Inspired by Kaz's project, I set out to build my own version that specifically converts research papers into audiobooks. I decided to adopt most of Kaz's architecture and leverage the power of Google Cloud's services to achieve my goal.

Building Your Own Audiobook Conversion Project

To build our own audiobook conversion project, we will follow a step-by-step approach similar to Kaz Sato's methodology. We will start by setting up a Google Cloud Storage bucket to store the PDFs that we want to convert into audiobooks. Then, we'll utilize the Vision API to extract the text from PDFs, which we will later convert into spoken words using text-to-speech technology. This process involves creating a cloud function, which allows us to run a small piece of code in the cloud when a specific event occurs. In our case, uploading a PDF to the cloud storage will trigger the cloud function that initiates the audiobook-making pipeline.

Customizing the Audiobook Text

After converting the PDFs into text, we need to decide which parts of the PDF text we want to include in the audiobook. For instance, we may want to include the body text and the title while excluding page numbers, references, or image Captions. To address this, we will need a custom machine-learning model that can identify and remove the unnecessary text. Kaz Sato accomplished this by training an Auto ML Tables model, which detects the garbage text, such as page headers or numbers, and allows us to extract the Relevant content. However, labeling the data for training the model manually can be time-consuming. To simplify the process, we will leverage font size as a proxy for identifying the body text, assuming that the most frequently used font size represents the main content of the research paper.

Generating Computer Voices with Google Cloud Text-to-Speech

To make the audiobooks more engaging, we can generate computer voices using the Google Cloud Text-to-Speech service. With over 220 voices in 40+ languages, we can choose the perfect Narrator for our audiobook. Selecting a suitable voice involves updating the code to reflect our preferred voice and configuring the parameters of the text-to-speech system. By automating the process, whenever we upload a PDF, an audiobook will be automatically generated using our chosen computer voice.

Listening to the Audiobook

Once we have completed the steps Mentioned above, we can listen to the audiobook generated from the research paper. The computer voice will Read aloud the transformed text, making it convenient to absorb the knowledge even while walking. This proves to be a breakthrough for individuals who wish to Continue learning during their daily walks.

Conclusion

In conclusion, transforming PDFs into audiobooks using machine learning techniques provides a convenient solution to the challenge of reading research papers while going for walks. By following the steps outlined in this article and building our own audiobook conversion project, we can easily enjoy the content of research papers while engaging in physical activities. The combination of computer vision and text-to-speech technology enables us to convert PDFs into spoken words, thereby expanding our opportunities for learning and personal development.