Visual Cues to Voice Cues

Abstract

The project is aimed at developing an object identifier for visually challenged. The proposed work uses ESP32CAM which acts as human eye. When visually challenged people navigate in known or unknown, indoor or outdoor environments, as they face troubles due to inaccessible infrastructure and social challenges, which in turn improve quality of Visually Impaired through visual information to the users. The idea is to capture real-time images of objects through ESP32CAM. Using the machine learning technique, object detection is done. The captured image is analyzed and converted into text. Further, the rule of text-tospeech is used, the text is then converted into sound using the Python module. The output of Text-to-speech is then amplified using an audio amplifier which is then heard through an earphone.