Towards Computer-Generated Cue-Target Mnemonics for E-Learning
A novel method to generate memory aids for general forms of knowledge is presented. Mnemonic phrases are constructed using constraints of phonetic similarity to learning material, grammar, semantics, and factual consistency. The method has been implemented in Python using the CMU Pronouncing Diction...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
2020
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| Online Access: | https://eprints.ums.edu.my/id/eprint/25406/1/Towards%20Computer-Generated%20Cue-Target%20Mnemonics%20for%20E-Learning%201.pdf |
| Summary: | A novel method to generate memory aids for general forms of knowledge is presented. Mnemonic phrases are constructed using constraints of phonetic similarity to learning material, grammar, semantics, and factual consistency. The method has been implemented in Python using the CMU Pronouncing Dictionary, the CYC AI knowledge base, and Kneser-Ney 5-gram probabilities built from the large-scale COCA text corpus. Initial tests have produced encouraging output. |
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