CUTLER Project
Published October 25, 2018 | Version v1
Conference paper Open

SemanPhone: Combining Semantic and Phonetic Word Association in Verbal Learning Context

Creators

  • 1. School of Software and Microelectronics NorthWestern Polytechnical University Xi'an, China
  • 2. Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
  • 3. Center for Ubiquitous Computing University of Oulu, Oulu, Finland

Description

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.

Notes

9. Lu Jiyan, Panos Kostakos, Mourad Oussalah, and Susanna Pirttikangas, "SemanPhone: Combining Semantic and Phonetic Word Association in Verbal Learning Context", in Proc. 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Barcelona, Spain, August 2018. (DOI: https://doi.org/10.1109/ASONAM.2018.8508827)

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Additional details

Funding

CUTLER – Coastal Urban developmenT through the LEnses of Resiliency 770469
European Commission