Papers by Stefano Mezza
ISO-Standard Domain-Independent Dialogue Act Tagging for Conversational Agents (C18-1)
Copied to clipboard
| Challenge: | Existing methods for DA annotation are incompatible with each other and do not cover all aspects necessary for open-domain human-machine interaction. |
| Approach: | They propose to map publicly available corpora to a subset of the ISO standard and create a task-independent training corpus for DA classification. |
| Outcome: | The proposed method can train a domain-independent DA tagger on out-of-domain conversational data and achieve robustness across different DA categories. |
A Multi-Dimensional, Cross-Domain and Hierarchy-Aware Neural Architecture for ISO-Standard Dialogue Act Tagging (2022.coling-1)
Copied to clipboard
| Challenge: | Dialogue Act tagging with ISO 24617-2 standard is a difficult task that requires multiple labels covering semantic, syntactic and pragmatic aspects of dialogue. |
| Approach: | They propose a neural architecture to increase Dialogue Act tagging accuracy by using low-frequency fine-grained tags. |
| Outcome: | The proposed model achieves state-of-the-art tagging results on DialogBank data set . it uses syntactic information in the form of Part-Of-Speech and dependency tags . |