Skip to main content
SpringerLink
Log in

Extractive Summarization of Broadcast News: Comparing Strategies for European Portuguese

  • Conference paper
Text, Speech and Dialogue (TSD 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4629))

Included in the following conference series:

Abstract

This paper presents the comparison between three methods for extractive summarization of Portuguese broadcast news: feature-based, Maximal Marginal Relevance, and Latent Semantic Analysis. The main goal is to understand the level of agreement among the automatic summaries and how they compare to summaries produced by non-professional human summarizers. Results were evaluated using the ROUGE-L metric. Maximal Marginal Relevance performed close to human summarizers. Both feature-based and Latent Semantic Analysis automatic summarizers performed close to each other and worse than Maximal Marginal Relevance, when compared to the summaries done by the human summarizers.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Furui, S.: Recent Advances in Automatic Speech Summarization. In: Proc. of the IEEE/ACL Workshop on Spoken Language Technology, IEEE, Los Alamitos (2006)

    Google Scholar 

  2. Murray, G., Renals, S., Carletta, J.: Extractive Summarization of Meeting Records. In: Proc. of the 9th EUROSPEECH - INTERSPEECH 2005 (2005)

    Google Scholar 

  3. Landauer, T.K., Foltz, P.W., Laham, D.: An Introduction to Latent Semantic Analysis. Discourse Processes 25 (1998)

    Google Scholar 

  4. Carbonell, J., Goldstein, J.: The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries. In: Proc. of the ACM SIGIR 1998 (1998)

    Google Scholar 

  5. Maskey, S., Hirschberg, J.: Comparing Lexical, Acoustic/Prosodic, Strucural and Discourse Features for Speech Summarization. In: Proc. of the 9th EUROSPEECH - INTERSPEECH 2005 (2005)

    Google Scholar 

  6. Neto, J.P., Meinedo, H., Amaral, R., Trancoso, I.: A System for Selective Dissemination of Multimedia Information. In: Proc. of the ISCA Workshop on Multilingual Spoken Document Retrieval 2003 (2003)

    Google Scholar 

  7. Trancoso, I., Neto, J.P., Meinedo, H., Amaral, R.: Evaluation of an alert system for selective dissemination of broadcast news. In: Proc. of the 8th EUROSPEECH - INTERSPEECH 2003 (2003)

    Google Scholar 

  8. Amaral, R., Meinedo, H., Caseiro, D., Trancoso, I., Neto, J.P.: Automatic vs. Manual Topic Segmentation and Indexation in Broadcast News. In: Proc. of the IV Jornadas en Tecnologia del Habla (2006)

    Google Scholar 

  9. Amaral, R., Trancoso, I.: Improving the topic indexation and segmentation modules of a media watch system. In: Proc. of the 8th International Conference on Spoken Language Processing (INTERSPEECH 2004 - ICSLP) (2004)

    Google Scholar 

  10. Mani, I.: Automatic Summarization. John Benjamins Publishing Company, Amsterdam (2001)

    MATH  Google Scholar 

  11. Edmundson, H.P.: New methods in automatic abstracting. Journal of the Association for Computing Machinery 16(2), 264–285 (1969)

    MATH  Google Scholar 

  12. Osborne, M.: Using Maximum Entropy for Sentence Selection. In: Proc. of the ACL Workshop on Automatic Summarization (2002)

    Google Scholar 

  13. Neto, J.L., Santos, A.D., Kaestner, C.A.A., Freitas, A.A.: Document Clustering and Text Summarization. In: Proc. of the 4th International Conference on Practical Applications of Knowledge Discovery and Data Mining (2000)

    Google Scholar 

  14. Gong, Y., Liu, X.: Generic Text Summarization Using Relevance Measure and Latent Semantic Analysis. In: Proc. of the ACM SIGIR 2001 (2001)

    Google Scholar 

  15. Lin, C.Y.: Looking for a Few Good Metrics: ROUGE and its Evaluation. In: Proc. Working Notes of NTCIR-4. vol. (supl. 2) (2004)

    Google Scholar 

  16. Laporte, E.: Resolução de Ambiguidades. In: Tratamento das Línguas por Computador – Uma introdução à Linguística Computacional e as suas aplicações. Editorial Caminho (2001)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. L2F/INESC ID Lisboa, Rua Alves Redol, 9, 1000-029 Lisboa, Portugal

    Ricardo Ribeiro & David Martins de Matos

Authors
  1. Ricardo Ribeiro
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David Martins de Matos
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Václav Matoušek Pavel Mautner

Rights and permissions

Reprints and permissions

Copyright information

© 2007 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ribeiro, R., de Matos, D.M. (2007). Extractive Summarization of Broadcast News: Comparing Strategies for European Portuguese. In: Matoušek, V., Mautner, P. (eds) Text, Speech and Dialogue. TSD 2007. Lecture Notes in Computer Science(), vol 4629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74628-7_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-74628-7_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74627-0

  • Online ISBN: 978-3-540-74628-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation