TY - GEN
T1 - Extracting the Semantic Representation of Chinese-Japanese Homophones with Word2Vec for Teaching Chinese as a Second/Foreign Language
AU - Lo, Min Chi
AU - Chang, Li Yun
AU - Tseng, Hou Chiang
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - The purpose of this study was to quantify the semantic distance between Chinese-Japanese homophones, and to further examine whether the traditional classification of Chinese-Japanese homophones reflects varying semantic distances. Ultimately, this study aimed to offer corresponding teaching suggestions for teachers’ reference. We introduced a novel approach to classifying Chinese-Japanese homophones by combining the Revised Hierarchical Model with the Word2Vec technology to extract semantic representations and calculate the semantic distance of meanings in Chinese-Japanese homophones across “Same”, “Overlap”, and “Different” types. Through cluster analysis of semantic distances, we found that semantic distance indeed reflects the traditional classification of Chinese-Japanese homophones. The “Same” type had the average semantic distance of 0, showing the high degree of similarity between the meanings in Chinese and Japanese within this category. The “Different” type had the greatest average semantic distance, indicating the lowest similarity. The “Overlap” type had the average semantic distance between the “Same” and “Different” types, representing the complex nature of this category. Based on these findings, this study proposed teaching suggestions to help Chinese teachers determine the teaching sequence among Chinese-Japanese homophones.
AB - The purpose of this study was to quantify the semantic distance between Chinese-Japanese homophones, and to further examine whether the traditional classification of Chinese-Japanese homophones reflects varying semantic distances. Ultimately, this study aimed to offer corresponding teaching suggestions for teachers’ reference. We introduced a novel approach to classifying Chinese-Japanese homophones by combining the Revised Hierarchical Model with the Word2Vec technology to extract semantic representations and calculate the semantic distance of meanings in Chinese-Japanese homophones across “Same”, “Overlap”, and “Different” types. Through cluster analysis of semantic distances, we found that semantic distance indeed reflects the traditional classification of Chinese-Japanese homophones. The “Same” type had the average semantic distance of 0, showing the high degree of similarity between the meanings in Chinese and Japanese within this category. The “Different” type had the greatest average semantic distance, indicating the lowest similarity. The “Overlap” type had the average semantic distance between the “Same” and “Different” types, representing the complex nature of this category. Based on these findings, this study proposed teaching suggestions to help Chinese teachers determine the teaching sequence among Chinese-Japanese homophones.
KW - Chinese-Japanese homophones
KW - semantic representation
KW - teaching Chinese as a second/foreign language
KW - Word2Vec
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U2 - 10.1007/978-3-031-65881-5_29
DO - 10.1007/978-3-031-65881-5_29
M3 - Conference contribution
AN - SCOPUS:85200683998
SN - 9783031658808
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 271
EP - 280
BT - Innovative Technologies and Learning - 7th International Conference, ICITL 2024, Proceedings
A2 - Cheng, Yu-Ping
A2 - Pedaste, Margus
A2 - Bardone, Emanuele
A2 - Huang, Yueh-Min
PB - Springer Science and Business Media Deutschland GmbH
T2 - 7th International Conference of Innovative Technologies and Learning, ICITL 2024
Y2 - 14 August 2024 through 16 August 2024
ER -