{'fraction_non_alphanumeric': 0.023832221163012392, 'fraction_numerical': 0.0, 'mean_word_length': 5.521739130434782, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Object Recognition and Hearing Assistive Technology Mobile Application using Convolutional Neural Network

Visual impairment is a condition that is globally recognize as a major concern due to its extensive disadvantage. The objective of the study is to develop an accessible and inclusive mobile application that will respond to the needs of the visually impaired community executed with Object Recognition and Text-to-Speech technology. Aside from this, it also upholds one of the many objectives of the United Nations' Sustainable Development Goals (SDG)---to provide inclusion for Person's with Disability (PWD), particularly in parts relating to the development towards education, growth and employment, and inequality. This objective is done with Convolutional Neural Network (CNN) algorithm that analyzes images to identify details which will be narrated to the user through Text-to-Speech. The study concludes that accessibility to technology for the visually impaired community is still young, thus further development must be accomplished.