Devanagari is a script used for several major languages such as Hindi, Sanskrit, Marathi and Nepali, and is used by more than 500 million people. Unconstrained Devanagari writing is more complex than English cursive due to the possible variations in the order, number, direction and shape of the constituent strokes. An on-line pen computing environment has numerous application in providing an easy human interjiace for a complex script like Devanagari. A Devanagari character recognition experiment with 20 different writers with each writer writing 5 samples of each character in a totally unconstrained way, has been conducted. An accuracy of 86.5% with no rejects is achieved through the combination of multiple classifiers that focus on either local on-line properties, or global off-line properties. Further improvements in performance are expected by using word-level contextual information. We are also exploring the use of writer dependent models to improve the recognition accuracy.

No abstract

Game-based learning is an approach to learning where gaming concepts are implemented in learning tasks designed by teachers. Here, learning activities boost a student’s commitment and inspiration to learn. Components of game-based learning include quizzes, point systems, leader boards, and classroom response systems. With the advancements in the field of education, game-based learning has proven that it is a utilitarian option in improving a student’s assessment where paper-based evaluation is not possible. Various Game-Based Learning Systems have been built previously and, in this paper, we have compared 11 existing models based on various factors like cost, quiz customization options, mobile support, etc. We have also pointed out the benefits and limitations of these systems. None of these systems give a complete set of all the features without being exorbitantly costly. So, we aspire to assemble a credible teaching project where all aspects would be included in a single application for the complete assessment of every student. The system has several key features like OCR, Speech to Text recognition, anti-cheating tools, and feedback after the quiz. For executing OCR, we have used OpenCV because of its extensive admiration and for Speech-to-Text Recognition (STR), we have adopted the SpeechRecognition library because it is quite adaptable. This system aims at reducing the workload of teachers by creating a test by scanning the questions with the help of OCR or by using STR so the teacher need not type the question and also by assessing students based on their scores

Normal human Beings can communicate with each other with the help of various different languages, however, the people who can't speak have different sign languages to communicate with others. But a major setback of sign language is that only people those who know sign language can communicate with them. Individuals habitually use gestures to interconnect. Gestures are used for directing to an individual, to get his devotion and convey statistics about temporal and spatial physiognomies. Gesticulating does not only elaborate verbal language, but it is part of the language production practice. In our paper we recommend a scheme which will be able to convert the sign language into words or sentences. The system takes inputs several hand gestures then processes its meaning and verifies it with the stored gestures in database and results the corresponding output on the screen.