An investigation of discrete Hidden Markov Models on handwritten short answer assessment system

Suwanwiwat, Hemmaphan, Das, Abhijit, Ferrer, Miguel, Pal, Umapada, and Blumenstein, Michael (2018) An investigation of discrete Hidden Markov Models on handwritten short answer assessment system. In: Proceedings of the International Conference on Pattern Recognition and Artificial Intelligence, pp. 144-149. From: ICPRAI 2018: International Conference on Pattern Recognition and Artificial Intelligence, May 14-17 2018, Montréal, Canada.

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Abstract

This paper presents an investigation of an off-line automatic assessment system utilising discrete Hidden Markov Models. A set of geometric features were extracted from handwritten words and were later classified by HMMs. There were two training datasets employed in the experiments; the first training dataset contained all correct answers to the questions whereas another training dataset contained both correct and incorrect answers to the questions. Datasets contained 3,000 and 3,400 handwritten samples, respectively. The experiments yielded promising results whereby the highest recognition rate of 91.90% with a 100% accuracy was achieved on our database.

Item ID: 54992
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: off-line automatic assessment system, Hidden Markov Models (HMMs), fixed-point arithmetic, geometric features
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ISBN: 978-1-895193-06-0
Date Deposited: 16 Aug 2018 00:11
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080106 Image Processing @ 30%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 70%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8999 Other Information and Communication Services > 899999 Information and Communication Services not elsewhere classified @ 100%
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