Language (Re)modelling: Towards Embodied Language Understanding
Ronen Tamari, Chen Shani, Tom Hope, Miriam R L Petruck, Omri Abend, Dafna Shahaf
Abstract
While natural language understanding (NLU) is advancing rapidly, today’s technology differs from human-like language understanding in fundamental ways, notably in its inferior efficiency, interpretability, and generalization. This work proposes an approach to representation and learning based on the tenets of embodied cognitive linguistics (ECL). According to ECL, natural language is inherently executable (like programming languages), driven by mental simulation and metaphoric mappings over hierarchical compositions of structures and schemata learned through embodied interaction. This position paper argues that the use of grounding by metaphoric reasoning and simulation will greatly benefit NLU systems, and proposes a system architecture along with a roadmap towards realizing this vision.- Anthology ID:
- 2020.acl-main.559
- Volume:
- Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Editors:
- Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 6268–6281
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.559
- DOI:
- 10.18653/v1/2020.acl-main.559
- Cite (ACL):
- Ronen Tamari, Chen Shani, Tom Hope, Miriam R L Petruck, Omri Abend, and Dafna Shahaf. 2020. Language (Re)modelling: Towards Embodied Language Understanding. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 6268–6281, Online. Association for Computational Linguistics.
- Cite (Informal):
- Language (Re)modelling: Towards Embodied Language Understanding (Tamari et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2020.acl-main.559.pdf