Abstract
Spoken languages are ever-changing, with new words entering them all the time. However, coming up with new words (neologisms) today relies exclusively on human creativity. In this paper we propose a system to automatically suggest neologisms. We focus on the Hebrew language as a test case due to the unusual regularity of its noun formation. User studies comparing our algorithm to experts and non-experts demonstrate that our algorithm is capable of generating high-quality outputs, as well as enhance human creativity. More broadly, we seek to inspire more computational work around the topic of linguistic creativity, which we believe offers numerous unexplored opportunities.- Anthology ID:
- 2020.findings-emnlp.442
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2020
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Trevor Cohn, Yulan He, Yang Liu
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4918–4929
- Language:
- URL:
- https://aclanthology.org/2020.findings-emnlp.442
- DOI:
- 10.18653/v1/2020.findings-emnlp.442
- Cite (ACL):
- Moran Mizrahi, Stav Yardeni Seelig, and Dafna Shahaf. 2020. Coming to Terms: Automatic Formation of Neologisms in Hebrew. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 4918–4929, Online. Association for Computational Linguistics.
- Cite (Informal):
- Coming to Terms: Automatic Formation of Neologisms in Hebrew (Mizrahi et al., Findings 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/2020.findings-emnlp.442.pdf
- Code
- stardeni36/coming-to-terms-automatic-formation-of-neologisms-in-hebrew