Detecting action items in multi-party meetings: annotation and initial experiments

Authors:
Matthew Purver;Patrick Ehlen;John Niekrasz
Affiliations:
Center for the Study of Language and Information, Stanford University, Stanford, CA;Center for the Study of Language and Information, Stanford University, Stanford, CA;Center for the Study of Language and Information, Stanford University, Stanford, CA
Venue:
MLMI'06 Proceedings of the Third international conference on Machine Learning for Multimodal Interaction
Year:
2006

Citing 7
Cited 6

The nature of statistical learning theory

The nature of statistical learning theory
Making large-scale support vector machine learning practical

Advances in kernel methods
Meeting Analysis: Findings from Research and Practice

HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 1 - Volume 1
Dialogue act modeling for automatic tagging and recognition of conversational speech

Computational Linguistics
Gemini: a natural language system for spoken-language understanding

ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Combining heterogeneous classifiers for word-sense disambiguation

WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
The necessity of a meeting recording and playback system, and the benefit of topic–level annotations to meeting browsing

INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction

Meeting adjourned: off-line learning interfaces for automatic meeting understanding

Proceedings of the 13th international conference on Intelligent user interfaces
Detecting Action Items in Meetings

MLMI '08 Proceedings of the 5th international workshop on Machine Learning for Multimodal Interaction
Disambiguating between generic and referential "you" in dialog

ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Multimodal subjectivity analysis of multiparty conversation

EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Automatically detecting action items in audio meeting recordings

SigDIAL '06 Proceedings of the 7th SIGdial Workshop on Discourse and Dialogue
Automatic annotation of dialogue structure from simple user interaction

MLMI'07 Proceedings of the 4th international conference on Machine learning for multimodal interaction

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents the results of initial investigation and experiments into automatic action item detection from transcripts of multi-party human-human meetings. We start from the flat action item annotations of [1], and show that automatic classification performance is limited. We then describe a new hierarchical annotation schema based on the roles utterances play in the action item assignment process, and propose a corresponding approach to automatic detection that promises improved classification accuracy while also enabling the extraction of useful information for summarization and reporting.