Abstract
In computational linguistics, it has been shown that hierarchical structures make language models (LMs) more human-like. However, the previous literature has been agnostic about a parsing strategy of the hierarchical models. In this paper, we investigated whether hierarchical structures make LMs more human-like, and if so, which parsing strategy is most cognitively plausible. In order to address this question, we evaluated three LMs against human reading times in Japanese with head-final left-branching structures: Long Short-Term Memory (LSTM) as a sequential model and Recurrent Neural Network Grammars (RNNGs) with top-down and left-corner parsing strategies as hierarchical models. Our computational modeling demonstrated that left-corner RNNGs outperformed top-down RNNGs and LSTM, suggesting that hierarchical and left-corner architectures are more cognitively plausible than top-down or sequential architectures. In addition, the relationships between the cognitive plausibility and (i) perplexity, (ii) parsing, and (iii) beam size will also be discussed.- Anthology ID:
- 2021.emnlp-main.235
- Original:
- 2021.emnlp-main.235v1
- Version 2:
- 2021.emnlp-main.235v2
- Version 3:
- 2021.emnlp-main.235v3
- Volume:
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Month:
- November
- Year:
- 2021
- Address:
- Online and Punta Cana, Dominican Republic
- Editors:
- Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2964–2973
- Language:
- URL:
- https://aclanthology.org/2021.emnlp-main.235
- DOI:
- 10.18653/v1/2021.emnlp-main.235
- Cite (ACL):
- Ryo Yoshida, Hiroshi Noji, and Yohei Oseki. 2021. Modeling Human Sentence Processing with Left-Corner Recurrent Neural Network Grammars. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 2964–2973, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- Modeling Human Sentence Processing with Left-Corner Recurrent Neural Network Grammars (Yoshida et al., EMNLP 2021)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2021.emnlp-main.235.pdf
- Code
- osekilab/rnng-eyetrack + additional community code