Abstract
This work presents a framework for word similarity evaluation grounded on cognitive sciences experimental data. Word pair similarities are compared to reaction times of subjects in large scale lexical decision and naming tasks under semantic priming. Results show that GloVe embeddings lead to significantly higher correlation with experimental measurements than other controlled and off-the-shelf embeddings, and that the choice of a training corpus is less important than that of the algorithm. Comparison of rankings with other datasets shows that the cognitive phenomenon covers more aspects than simply word relatedness or similarity.- Anthology ID:
- W17-5304
- Volume:
- Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP
- Month:
- September
- Year:
- 2017
- Address:
- Copenhagen, Denmark
- Editors:
- Samuel Bowman, Yoav Goldberg, Felix Hill, Angeliki Lazaridou, Omer Levy, Roi Reichart, Anders Søgaard
- Venue:
- RepEval
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 21–26
- Language:
- URL:
- https://aclanthology.org/W17-5304
- DOI:
- 10.18653/v1/W17-5304
- Cite (ACL):
- Jeremy Auguste, Arnaud Rey, and Benoit Favre. 2017. Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks. In Proceedings of the 2nd Workshop on Evaluating Vector Space Representations for NLP, pages 21–26, Copenhagen, Denmark. Association for Computational Linguistics.
- Cite (Informal):
- Evaluation of word embeddings against cognitive processes: primed reaction times in lexical decision and naming tasks (Auguste et al., RepEval 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-5304.pdf