Even at a young age, Vedant Sheel, a Grade 9 student at Saugeen District Senior School (SDSS) is a force to be reckoned with as he excels in computer science, which he hopes to pursue as a career.
Sheel of the Bluewater District School Board (BWDSB) recently competed at the National Science Fair held in Edmonton, where his project, ‘A Voice for the Voiceless’, gained national recognition with a Silver medal. In addition, he was also awarded a Shad Canada Scholarship Award for $3,000 in the Intermediate category, was also awarded a silver excellence award medal and certificate, a University of Alberta Bronze medalist entrance scholarship worth $1,500, and a Western University Silver medalist scholarship worth $2,000.
His project is a real-time American Sign Language (ASL) to text-to-voice translator using Python programming language. It works by a user performing various sign language letters in front of a computer, and by using various methods, the computer makes a prediction as to which letter the user is performing. He created a Graphical User Interface as the final output which displays the letter based on the ASL letter performed by the user and then saves a letter in an empty string to turn into a word. Adding it the computer provides four different dictionary suggestions for similarly spelled words, one gesture for backspace, and the next letter of the alphabet. Also, a speak button outputs the text as a computer-generated voice.
Unlike humans, computers don’t recognize objects. All they see is an array of pixels with certain features such as brightness, contrast, saturation, and RBG colors. His project was to provide a computer with a vision to see using these features. In other words, his project has him teaching a computer how to interpret and translate sign language into English text. The purpose is to help someone who doesn’t understand American Sign Language (ASL) to communicate with someone who does use the language.
The project, that he began a year and a half ago, occurred to him when he thought about how deaf people use sign language, but few people understand it. He imagined that, when the project was completed, a mobile app would be available to help someone who doesn’t understand American Sign Language (ASL) to communicate with someone who uses it.
He said the project’s two main aspects are machine learning (Artificial intelligence) and computer vision.
