Abstract
This paper introduces a novel method for empirically evaluating the relationship between the phonological and semantic similarity of linguistic units using embedding spaces. Chinese character homophones are used as a proof-of-concept. We employ cosine similarity as a proxy for semantic similarity between characters, and compare relationships between phonologically-related characters and baseline characters (chosen as similar-frequency characters). We show there is a strongly statistically significant positive semantic relationship among different Chinese characters at varying levels of sound-sharing. We also perform some basic probing using t-SNE and UMAP visualizations, and indicate directions for future applications of this method.- Anthology ID:
- 2024.acl-srw.34
- Volume:
- Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Xiyan Fu, Eve Fleisig
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 391–396
- Language:
- URL:
- https://aclanthology.org/2024.acl-srw.34
- DOI:
- Cite (ACL):
- Sophie Wu, Anita Zheng, and Joey Chuang. 2024. Homophone2Vec: Embedding Space Analysis for Empirical Evaluation of Phonological and Semantic Similarity. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop), pages 391–396, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Homophone2Vec: Embedding Space Analysis for Empirical Evaluation of Phonological and Semantic Similarity (Wu et al., ACL 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.acl-srw.34.pdf