LIA: A Natural Language Programmable Personal Assistant

Igor Labutov, Shashank Srivastava, Tom Mitchell


Abstract
We present LIA, an intelligent personal assistant that can be programmed using natural language. Our system demonstrates multiple competencies towards learning from human-like interactions. These include the ability to be taught reusable conditional procedures, the ability to be taught new knowledge about the world (concepts in an ontology) and the ability to be taught how to ground that knowledge in a set of sensors and effectors. Building such a system highlights design questions regarding the overall architecture that such an agent should have, as well as questions about parsing and grounding language in situational contexts. We outline key properties of this architecture, and demonstrate a prototype that embodies them in the form of a personal assistant on an Android device.
Anthology ID:
D18-2025
Volume:
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
Month:
November
Year:
2018
Address:
Brussels, Belgium
Editors:
Eduardo Blanco, Wei Lu
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
145–150
Language:
URL:
https://aclanthology.org/D18-2025
DOI:
10.18653/v1/D18-2025
Bibkey:
Cite (ACL):
Igor Labutov, Shashank Srivastava, and Tom Mitchell. 2018. LIA: A Natural Language Programmable Personal Assistant. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 145–150, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
LIA: A Natural Language Programmable Personal Assistant (Labutov et al., EMNLP 2018)
Copy Citation:
PDF:
https://aclanthology.org/D18-2025.pdf