Posts by Collection

Portfolio item number 1

Short description of portfolio item number 1

Portfolio item number 2

Short description of portfolio item number 2

Feature Structures in the Wild: A Case Study in Mixing Traditional Linguistic Knowledge Representation with Neural Language Models

Published in Proceedings of the ACL-21 Workshop on Computing Semantics with Types, Frames and Related Structures, 2021

This paper briefly presents an evaluation of three models: a domain-specific one based upon typed feature structures, a neural language model, and a mixture of the two, on an unseen but in-domain corpus of user queries in the context of a dialogue classification task. We find that the mixture performs the best, which opens the door to a potentially new application of neural language models. A further examination of the domain- We also consider the inner workings of the domainspecific model in more detail, as well as how it came into being, from an ethnographic perspective. This has changed our perspective on the potential role of structured representations in the future of dialogue systems, and suggests that formal research in this area may have a new role to play in validating and coordinating ad hoc dialogue systems development.

Recommended citation: Penn, Gerald and Shi, Ken. (2021). "Feature Structures in the Wild: A Case Study in Mixing Traditional Linguistic Knowledge Representation with Neural Language Models." Proceedings of the ACL-21 Workshop on Computing Semantics with Types, Frames and Related Structures. 53(7). https://aclanthology.org/2021.cstfrs-1.6.pdf

Voice assistants in vehicles: A case study in mixing traditional linguistic knowledge representations with neural language models

Published: December 02, 2022

Voice Assistants in Vehicles has been a popular application of dialogue systems, and there have been many different approaches for this task. This talk will briefly present an evaluation of three models: a domain-specific one based upon typed feature structures, a neural language model, and a mixture of the two, on an unseen but in-domain corpus of user queries in the context of a dialogue classification task. The finding opens the door to a potentially new application of neural language models. The study has changed our perspective on the potential role of structured representations in the future of dialogue systems, and suggests that formal research in this area may have a new role to play in validating and coordinating ad hoc dialogue systems development.

Teaching Assistantship 2023 Fall

Graduate / Undergraduate Courses, University of Toronto, 2023

Two Teaching Assistantships: CSC485/2501 in Department of Computer Science; and ESC180 in Department of Applied Science and Engineering.