Skip to main content

Research Repository

Advanced Search

Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue (2022)
Journal Article
Duran, N., Battle, S., & Smith, J. (in press). Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue. Communication Methods and Measures, https://doi.org/10.1080/19312458.2021.2020229

We present the Conversation Analysis Modeling Schema (CAMS), a novel dialogue labeling schema that combines the Conversation Analysis concept of Adjacency Pairs, with Dialogue Acts. The aim is to capture both the semantic and syntactic structure of d... Read More about Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue.

Sentence encoding for Dialogue Act classification (2021)
Journal Article
Duran, N., Battle, S., & Smith, J. (in press). Sentence encoding for Dialogue Act classification. Natural Language Engineering, https://doi.org/10.1017/S1351324921000310

In this study, we investigate the process of generating single-sentence representations for the purpose of Dialogue Act (DA) classification, including several aspects of text pre-processing and input representation which are often overlooked or under... Read More about Sentence encoding for Dialogue Act classification.

Conversation analysis structured dialogue for multi-domain dialogue management (2018)
Presentation / Conference
Duran, N., & Battle, S. (2018, December). Conversation analysis structured dialogue for multi-domain dialogue management. Paper presented at The International Workshop on Dialogue, Explanation and Argumentation in Human-Agent Interaction (DEXAHAI), Southampton

Dialogue state tracking is a vital component of task-oriented dialogue systems. Often, dialogue states are constrained by their target domains entity's, slots and values. Adding new domains and knowledge may require laborious hand-crafting or retrain... Read More about Conversation analysis structured dialogue for multi-domain dialogue management.

Probabilistic word association for dialogue act classification with recurrent neural networks (2018)
Book Chapter
Duran, N., & Battle, S. (2018). Probabilistic word association for dialogue act classification with recurrent neural networks. In C. Jayne, A. Likas, L. Iliadis, & G. Boracchi (Eds.), Engineering Applications of Neural Networks, 229-239. Springer

The identification of Dialogue Acts (DA) is an important aspect in determining the meaning of an utterance for many applications that require natural language understanding, and recent work using recurrent neural networks (RNN) has shown promising re... Read More about Probabilistic word association for dialogue act classification with recurrent neural networks.