Abstract
We propose a general framework to study language emergence through signaling games with neural agents. Using a continuous latent space, we are able to (i) train using backpropagation, (ii) show that discrete messages nonetheless naturally emerge. We explore whether categorical perception effects follow and show that the messages are not compositional.- Anthology ID:
- 2020.acl-main.433
- 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:
- 4794–4800
- Language:
- URL:
- https://aclanthology.org/2020.acl-main.433
- DOI:
- 10.18653/v1/2020.acl-main.433
- Cite (ACL):
- Nur Geffen Lan, Emmanuel Chemla, and Shane Steinert-Threlkeld. 2020. On the Spontaneous Emergence of Discrete and Compositional Signals. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 4794–4800, Online. Association for Computational Linguistics.
- Cite (Informal):
- On the Spontaneous Emergence of Discrete and Compositional Signals (Geffen Lan et al., ACL 2020)
- PDF:
- https://preview.aclanthology.org/landing_page/2020.acl-main.433.pdf
- Code
- 0xnurl/signaling-auto-encoder