In my project prototype, I will have a JD head that provides interaction with a student who wants (needs?) to learn some remedial math. My design approach is that the bot interface will serve two purposes:
1. a friendly, engaging interface with the student
2. essentially a data collection device observing student understanding through
a. spoken responses from student to questions and prompts posed by JD
b. written responses from student as problem solutions are attempted
by the student
So, from a prototype perspective, we probably have "friendly and engaging" covered (I have to admit being excited about learning more about EZ-AI). However, I believe that the handwriting recognition (real-time) will be tough. I have taken a look at open source tesseract, but don't see it as a practical solution. I believe that product compares written characters to some existing database of alphabetic character representations and does so offline. What's needed here is a software tool that real time determines the character written by the student.
Part of the solution is that, when a student is first introduced to a JD head in the lab, part of the get-to-know-you interchange will be JD asking the student to write the numerals 0 through 9, and the letters x, y, a, b, and c. That might be all we need in remedial math. So we can store, for each student, a mini-database that contains both written and verbal expressions of each of the numerals and the selected letters.
After a bunch of research, it looks like the only (real time) solutions is to use a neural network application running on the associated PC. I've found some research done in 2000 involving methods and coding for "on-line" recognition of handwritten signatures that would see to be more than enough processing power for this prototype
My question: Are you aware of any software tool that could use digital camera input to recognize in real time handwritten characters?
Thanks for any suggestions!