From extractive to abstractive meeting summaries: can it be done by sentence compression?

Authors:
Fei Liu;Yang Liu
Affiliations:
The University of Texas at Dallas, Richardson;The University of Texas at Dallas, Richardson
Venue:
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Year:
2009

Citing 9
Cited 5

Summarization beyond sentence extraction: a probabilistic approach to sentence compression

Artificial Intelligence
Edit detection and parsing for transcribed speech

NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Supervised and unsupervised learning for sentence compression

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
A statistical approach to automatic speech summarization

EURASIP Journal on Applied Signal Processing
A global optimization framework for meeting summarization

ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
A skip-chain conditional random field for ranking meeting utterances by importance

EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Summarizing speech without text using hidden Markov models

NAACL-Short '06 Proceedings of the Human Language Technology Conference of the NAACL, Companion Volume: Short Papers
Global inference for sentence compression an integer linear programming approach

Journal of Artificial Intelligence Research
Sentence compression as tree transduction

Journal of Artificial Intelligence Research

Long story short - Global unsupervised models for keyphrase based meeting summarization

Speech Communication
Abstractive summarization of voice communications

LTC'09 Proceedings of the 4th conference on Human language technology: challenges for computer science and linguistics
Automatic summarization

HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts of ACL 2011
Query snowball: a co-occurrence-based approach to multi-document summarization for question answering

HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
A two-step approach to sentence compression of spoken utterances

ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

Most previous studies on meeting summarization have focused on extractive summarization. In this paper, we investigate if we can apply sentence compression to extractive summaries to generate abstractive summaries. We use different compression algorithms, including integer linear programming with an additional step of filler phrase detection, a noisy-channel approach using Markovization formulation of grammar rules, as well as human compressed sentences. Our experiments on the ICSI meeting corpus show that when compared to the abstractive summaries, using sentence compression on the extractive summaries improves their ROUGE scores; however, the best performance is still quite low, suggesting the need of language generation for abstractive summarization.