A multi-classifier approach to dialogue act classification using function words

Authors:
James O'Shea;Zuhair Bandar;Keeley Crockett
Affiliations:
Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom;Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom;Department of Computing and Mathematics, Manchester Metropolitan University, United Kingdom
Venue:
Transactions on Computational Collective Intelligence VII
Year:
2012

Citing 19
Cited 0

An introduction to neural computing

An introduction to neural computing
C4.5: programs for machine learning

C4.5: programs for machine learning
CiteSeer: an autonomous Web agent for automatic retrieval and identification of interesting publications

AGENTS '98 Proceedings of the second international conference on Autonomous agents
A vector space model for automatic indexing

Communications of the ACM
Information Retrieval

Information Retrieval
Induction of Decision Trees

Machine Learning
Dialogue act modeling for automatic tagging and recognition of conversational speech

Computational Linguistics
Learning dialog act processing

COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Latent semantic analysis for dialogue act classification

NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Dialogue act recognition with Bayesian networks for Dutch dialogues

SIGDIAL '02 Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2
Training a Dialogue Act Tagger for human-human and human-computer travel dialogues

SIGDIAL '02 Proceedings of the 3rd SIGdial workshop on Discourse and dialogue - Volume 2
Sentence Similarity Based on Semantic Nets and Corpus Statistics

IEEE Transactions on Knowledge and Data Engineering
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Health dialog systems for patients and consumers

Journal of Biomedical Informatics - Special issue: Dialog systems for health communications
Semantic text similarity using corpus-based word similarity and string similarity

ACM Transactions on Knowledge Discovery from Data (TKDD)
Intelligent agents for the smart grid

Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
A machine learning approach to speech act classification using function words

KES-AMSTA'10 Proceedings of the 4th KES international conference on Agent and multi-agent systems: technologies and applications, Part II
Using a slim function word classifier to recognise instruction dialogue acts

KES-AMSTA'11 Proceedings of the 5th KES international conference on Agent and multi-agent systems: technologies and applications
Error analysis of dialogue act classification

TSD'05 Proceedings of the 8th international conference on Text, Speech and Dialogue

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper extends a novel technique for the classification of sentences as Dialogue Acts, based on structural information contained in function words. Initial experiments on classifying questions in the presence of a mix of straightforward and "difficult" non-questions yielded promising results, with classification accuracy approaching 90%. However, this initial dataset does not fully represent the various permutations of natural language in which sentences may occur. Also, a higher Classification Accuracy is desirable for real-world applications. Following an analysis of categorisation of sentences, we present a series of experiments that show improved performance over the initial experiment and promising performance for categorising more complex combinations in the future.