Cognitive Analysis for Reading and Writing of Bengali Conjuncts
Proceedings of the International Joint Conference on Neural Networks
In this paper, we study the difficulties arising in reading and writing of Bengali conjunct characters by human-beings. Such difficulties appear when the human cognitive system faces certain obstructions in effortlessly reading/writing. In our computer-based investigation, we consider the reading/writing difficulty analysis task as a machine learning problem supervised by human perception. To this end, we employ two distinct models: (a) an auto-derived feature-based Inception network and (b) a hand-crafted feature-based SVM (Support Vector Machine). Two commonly used Bengali printed fonts and three contemporary handwritten databases are used for collecting subjective opinion scores from human readers/writers. On this corpus, which contains the perceptive ground-truth opinion of reading/writing complications, we have undertaken to conduct the experiments. The experimental results obtained on various types of conjunct characters are promising.
Adak, Chandranath; Chaudhuri, Bidyut B.; and Blumenstein, Michael, "Cognitive Analysis for Reading and Writing of Bengali Conjuncts" (2018). Conference Articles. 48.