SemanPhone : combining semantic and phonetic word association in verbal learning context

Jiyan, Lu; Kostakos, Panos; Oussalah, Mourad; Pirttikangas, Susanna (2018-10-25)
 
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https://doi.org/10.1109/ASONAM.2018.8508827

Jiyan, Lu
Kostakos, Panos
Oussalah, Mourad
Pirttikangas, Susanna
IEEE Computer Society
25.10.2018

L. Jiyan, P. Kostakos, M. Oussalah and S. Pirttikangas, "SemanPhone: Combining Semantic and Phonetic Word Association in Verbal Learning Context," 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Barcelona, 2018, pp. 1047-1052. doi: 10.1109/ASONAM.2018.8508827

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doi:https://doi.org/10.1109/ASONAM.2018.8508827
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https://urn.fi/URN:NBN:fi-fe2019042913473
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Abstract

This paper proposes an effective way to discover and memorize new English vocabulary based on both semantic and phonetic associations. The method we proposed aims to automatically find out the most associated words of a given target word. The measurement of semantic association was achieved by calculating cosine similarity of two-word vectors, and the measurement of phonetic association was achieved by calculating the longest common subsequence of phonetic symbol strings of two words. Finally, the method was implemented as a web application.

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