Third Eye: Object Recognition and Speech Generation for Visually Impaired

Abstract

Detecting and recognizing the objects and generating speech about the objects helps visually impaired in a great way in understanding their surroundings. Required a mechanism to assist the visually impaired person to travel independently with the ability to identify objects in their path, and the ability to generate speech describing the objects detected in the scene. This can be achieved with the help of YOLOv5 image detection model and text to speech converters such as gTTS and pyttsx3 modules in python. The proposed method called Third Eye, giving better accuracy in detection and speech generation to help the visually impaired people Compared to existing approaches. YOLO v5 is trained on custom dataset of 15 objects along with MS COCO 2017 Dataset of 80 objects (95 objects overall). The output labels of the model are transformed to text and later converted to audio format and are presented to the visually impaired, through a speaker. We compared two python libraries for audio conversion, one is pyttsx3, and the other is gTTS.