Object Detection System for the Blind with Voice Command and Guidance

Abstract

As object recognition technology has developed recently, various technologies have been applied to autonomous vehicles, robots, and industrial facilities. However, the benefits of these technologies are not reaching the visually impaired, who need it the most. In this paper, we proposed an object detection system for the blind using deep learning technologies. We use voice recognition technology in order to know what objects a blind person wants, and then to find the objects via object recognition. Furthermore, a voice guidance technique is used to inform sightimpaired persons as to the location of objects. The object recognition deep learning model utilizes the Single Shot Multibox Detector (SSD) neural network architecture, and voice recognition is designed through speech-to-text (STT) technology. In addition, a voice announcement is synthesized using text-to-speech (TTS) to make it easier for the blind to get information about objects. The control system is based on the Arduino microprocessor. As a result, we implement an efficient object-detection system that helps the blind find objects in a specific space without help from others, and the system is analyzed through experiments to verify performance.