Table of Contents
Dynamic Web Content Reader Application for Low Vision Patients using Python: The complexity of the existing Braille system for the visually impaired people is that it requires the text to be translated to Braille literature. Translating a book or a document into Braille literature is a complex, time consuming and more expensive process.
Day-to-day information cannot be translated into Braille literature. To ease this process of reading for the visually impaired people, this prototype has been proposed. Using this prototype, text information can be converted into its equivalent audio format. This is done using python libraries with the concept of Natural Language Processing, Web Mining, Text-to-Speech. It is portable and easy to use thus providing a better reading experience to the visually challenged people as enjoyed by their sighted peers.
Remaining section describe about Existing System and Proposed System.
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II. EXISTING SYSTEM
Dynamic Web Content Reader Application for Low Vision Patients using Python: The Existing system done by integrating camera module and speakers to Raspberry Pi 3 model B which is a credit card sized single board computer. Also, two other software called Tesseract and TTS engine (Text to Speech synthesizer) is installed to the Raspbian OS. Principally, the camera captures the image and stores it as an image file with a .jpg extension. The OCR engine converts it from image file to text file by extracting the numbers and characters of the language. The file is given as an input to a python program which gives a translated speech output using Google text to speech engine.
Text-to speech device consisted of three main modules, the image processing module, word correction module, and voice processing modules. Image processing module sets the object position, focus and illumination camera, taking pictures, and converting the image into text. Word correction module makes corrections to the output image processing module to improve accuracy by matching with Indonesian dictionary. Voice processing module changes the writing into sound and process it with specific physical characteristics so that the sound can be understood.
The input image captured by the camera has a size of 5 MPI (2592 x 1944 pixels) or 215 ppi(pixels per inch). Based on the specifications of the Tesseract OCR engine, the minimum character size that can be read is 20 pixels uppercase letters. Tesseract OCR accuracy will decrease with the font size of 10pt.
The image is taken by the user via GPIO pin that are connected to the tactile key using interrupt function. Furthermore, the picture is taken by using raspistill program with sharpness mode to sharpen the image. The resulting image has a .jpg format with a resolution of 2592 x 1944 pixels.
Word correction module gets input from the image processing module in the form of text from the image processing module.
Image processing module can’t define truth or falsity of the word output, so that the correction module of this word, correction for whole words output from the image processing requires module. In order to improve the accuracy of the output image processing module, to design the word correction module.
The main disadvantage of the existing system is highly expensive. And the portability of the Device is very difficult. The Existing system using only converts the printed content. Also, the capturing paper size is A4 only. The Device Takes more time to convert the scanned Documents. If any problem occurred in the specific part of the device, it will affect the total setup.
III. PROPOSED SYSTEM
The complexity of the existing Braille system for the visually impaired people is that it requires, the text to be translated to Braille literature. Translating a book or a document into Braille literature is a complex, time consuming and more expensive process. Day-to-day information cannot be translated into Braille literature. To ease this process of reading for the visually impaired people, this prototype has been proposed. Benefits of the visually impaired are not necessary to learn any new language. The visually impaired can easily understand because different languages converted into native languages and hearable audio output. In the Proposed system, all external devices are avoided. In the Existing System, only can convert specific languages like Tamil and English. But in the proposed system, establish multiple conversion of languages like English, Arab, Japanese, French etc. In the Proposed System, convert the dynamic web content using web mining and Natural Language Processing concepts. It is easy to use and portable. All kind of people can use this application. And content can easily understand by the visually impaired persons also other language peoples are able to understand the different languages in our native languages.
IV. DESIGN & IMPLEMENTATION
“Dynamic Web Content Reader Application for Low Vision Patients using Python”: Our designed Project is called Web Reader, a simple application with the text to speech functionality. The system was developed using web mining and NLP concepts using python.
The application is divided into three modules – the main application module which includes the basic GUI components which handles the basic operations of the application such as input of parameters for conversion either via file or direct keyboard input.
The second module, Requesting the targeted website using urllib to fetch by using GET method and read the content as object (page as Object). Separate content from DOM object by using bs4 and find the targeted object.
The third module, Converting DOM object as a string. Parse string to the textblob. Finally Set output language & store in array (language conversion) and loop the string converted to audio.
Web Reader converts Dynamic web content to Audio output in native Language in the application. It provides multiple language conversion into native language. Web Reader loads the content from the website and the Language Conversion procedure starts automatically.
Web Reader contains an exceptional function that gives the user the choice of saving its already converted text to any part of the local machine in an audio format; this allows the user to copy the audio format to any of his/her audio devices, so that they can hence forth treat it as an audio book.
A. Requests Requests will allow you to send HTTP/1.1 requests using Python. With it, you can add content like headers, form data, multipart files, and parameters via simple Python libraries. It also allows you to access the response data of Python in the same way.
B. Bs4 BeautifulSoup 4. Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work
C. Textblob TextBlob is a Python (2 and 3) library for processing textual data. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more.
D. gtts gTTS (Google Text-to-Speech), a Python library and CLI tool to interface with Google Translates text-to-speech API. Writes spoken mp3 data to a file, a file-like object (bytestring) for further audio manipulation, or stdout. It features flexible pre-processing and tokenizing, as well as automatic retrieval of supported languages.
E. pydub Manipulate audio with an simple and easy high level interface.
F. lxml The lxml XML toolkit is a Pythonic binding for the C libraries libxml2 and libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python API, mostly compatible but superior to the well-known ElementTree API.
G. OS: The OS module in Python provides a way of using operating system dependent functionality. The functions that the OS module provides allows you to interface with the underlying operating system that Python is running on – be that Windows, Mac or Linux.
The Requests library used to Requesting the targeted website using urllib to fetch by using GET method and read the content as object (page as Object). Separate content from DOM object by using bs4 and find the targeted object.
Web Reader Application is a flexible robust dynamic growing aspect of modern computer era and it is increasingly playing a more significance role in the way we interact with the system and interfaces which is based on platform independent concept. We have identified the various operations and processes involved in text to speech synthesis. We have also developed a very simple and attractive graphical user interface which allows the user to choose the language in the application. Our system interfaces with a text to speech engine developed for Arabic, Japanese, english. In future, we plan to make efforts to create engines for conversion of one language to other make text to speech technology more accessible to a wider range. Accuracy of the software is excellent in the context of its ability to work in real-life environment. We also have plans to make it a web based real-time synthesis system, so that its uses can get more expanded.