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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Allan, J. Allen, T. Sherkat, N. Halstead, P. |
| Copyright Year | 2001 |
| Description | Author affiliation: Dept. of Comput., Nottingham Trent Univ., UK (Allan, J.) |
| Abstract | An extensive literature survey on automated assessment and handwriting recognition has shown that no work has been done in addressing the area of assessment of handwritten exam scripts. We therefore introduce the novel concept of applying image extraction and cursive script recognition (CSR) techniques to the area of automated assessment. We demonstrate the potential for using a holistic CSR engine as the input process for a system capable of automatically scoring handwritten responses to multi-choice questions. This innovative system utilises the constrained nature of simple multiple choice questions to enhance the recognition rate of the handwritten response. Fifty writers were chosen to answer eight multiple choice questions and results show that the system yields an average 83% CSR word accuracy, which enables the system to score over 54% of all response with 99% confidence. |
| Sponsorship | IAPR |
| Starting Page | 926 |
| Ending Page | 930 |
| File Size | 377189 |
| Page Count | 5 |
| File Format | |
| ISBN | 0769512631 |
| DOI | 10.1109/ICDAR.2001.953921 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-09-13 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Handwriting recognition Writing Text recognition Ordinary magnetoresistance Iris Image recognition Engines Software testing Natural language processing Keyboards |
| Content Type | Text |
| Resource Type | Article |
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