2020
DOI: 10.48550/arxiv.2011.09954
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Persuasive Dialogue Understanding: the Baselines and Negative Results

Abstract: Persuasion aims at forming one's opinion and action via a series of persuasive messages containing persuader's strategies. Due to its potential application in persuasive dialogue systems, the task of persuasive strategy recognition has gained much attention lately. Previous methods on user intent recognition in dialogue systems adopt recurrent neural network (RNN) or convolutional neural network (CNN) to model context in conversational history, neglecting the tactic history and intra-speaker relation. In this … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2022
2022

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 22 publications
0
1
0
Order By: Relevance
“…Chen [14] investigated a state-of-the-art natural language processing model, transformer-based coupled with Conditional Random Field (CRF). When comparing this architecture with several baseline systems, the model's limitations for persuasion strategy recognition become apparent.…”
Section: Related Workmentioning
confidence: 99%
“…Chen [14] investigated a state-of-the-art natural language processing model, transformer-based coupled with Conditional Random Field (CRF). When comparing this architecture with several baseline systems, the model's limitations for persuasion strategy recognition become apparent.…”
Section: Related Workmentioning
confidence: 99%