Traffic Sign Board Recognition and Multilingual Voice Alert System

Abstract— Roads around the world bring constant risks. Spotting signs early helps avoid crashes while driving. Fast movement, bad weather, or lack of attention often make visual detection hard. A new approach uses spoken warnings to guide drivers safely. It finds and marks road signs instantly using live video. Smart algorithms process images quickly, focusing on shapes and colours. Instead of slow methods, this tool chooses speed without losing accuracy. Voice cues come right after spotting a sign. The tech behind it? A version of YOLO built for fast tracking. Real-time performance matters most here - delays could cost lives. Not just visuals - sound plays a role too when the system spots road signs. Drivers get spoken updates about things like speed numbers, stops, or alerts as they happen. This runs live through video analysis that keeps up with movement on screen. Code stitched together using tools such as OpenCV guides how images are studied. A Python backbone powers decision steps behind what shows and speaks. Voice output emerges via speech generation software tied into detection results. What you hear matches what the camera sees without delay. This method catches key signals quickly, using basic equipment instead of costly tools - so it fits well into driver aids and modern traffic networks. Keywords—Traffic Sign Detection, YOLOv8, Object Detection, Computer Vision, Driver Assistance System, Voice Alert