A three-stage disfluency classifier for multi party dialogues

Proceedings of the 6th International Conference on Language Resources and Evaluation, LREC 2008

Volumn , Issue , 2008, Pages 2681-2686

  Mieskes, Margot ^a   Strube, Michael ^b  

^a European Media Laboratory GmbH   (Germany)

^b EML Research gGmbH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DISFLUENCIES; MULTI-PARTY DIALOGUES; REGULAR EXPRESSIONS; THREE-STAGE SYSTEM; TWO MACHINES;

LEARNING SYSTEMS;

EID: 84976238242     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Baron, Don, Elizabeth Shriberg & Andreas Stolcke (2002). Automatic punctuation and disfluency detection in multi-party meetings using prosodic and lexical cues. In Proceedings of the International Conference on Spoken Language Processing, Vol. 2, pp. 949-952. Denver, USA.
2. Brill, Eric (1994). Some advances in transformation based partof-speech tagging. In Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, Wash., 1-4 August 1994, pp. 722-727.
3. Cohen, Jacob (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20:37-46.
4. Core, Mark G. & Lenhart K. Schubert (1999). A syntactic framework for speech repairs and other disruptions. In Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, College Park, Md., 20-26 June 1999, pp. 413-420.
5. Fleiss, Joseph L. (1971). Measuring nominal scale agreement among many raters. Psychological Bulletin, 76(5):378-382.
6. Godfrey, John J., Edward Holliman & J. McDaniel (1992). Switchboard: Telephone speech corpus for research and development. In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, San Francisco, Cal., USA, pp. 517-520.
7. Heeman, Peter A. & James F. Allen (1999). Speech repairs, intonational phrases, and discourse markers: Modeling speakers' utterances in spoken dialogue. Computational Linguistics, 25(4):527-571.
8. Janin, Adam, Don Baron, Jane Edwards, Dan Ellis, David Gelbart, Nelson Morgan, Barbara Peskin, Thilo Pfau, Elizabeth Shriberg, Andreas Stolcke & Chuck Wooters (2003). The ICSI meeting corpus. In Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Hong Kong, China, 6-10 April 2003, pp. 364-367.
9. Johnson, Mark & Eugene Charniak (2004). A tag-based noisy channel model of speech repairs. In Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics, Barcelona, Spain, 21-26 July 2004, pp. 33-39.
10. Lendvai, Piroska, Antal van den Bosch & Emiel Krahmer (2003). Memory-based disfluency chunking. In Proceedings of Disfluency in Spontaneous Speech Workshop Göteborg University, Sweden, September 5-8, 2003, pp. 63-66.
11. Lickley, Robin J. (2001). Dialogue moves and disfluency rates. In ITRW on Disfluency in Spontaneous Speech, Edinburgh, Scotland, UK, August 29-31, 2001, pp. 93-96.
12. Liu, Yang, Elizabeth Shriberg, Andreas Stolcke & Mary Harper (2005). Comparing HMM, maximum entropy, and conditional random fields for disfluency detection. In P roceedings of the 9th Europeach Conference on Speech Communication and Technology (INTERSPEECH'05), Lisboa, Portugal, 4-8 September 2005.
13. Nakatani, Christine & Julia Hirschberg (1993). A speech-first model for repair detection and correction. In Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics, Columbus, Ohio, 22-26 June 1993, pp. 46-53.
14. Pakhomov, Sergey & Guergana Savova (1999). Filled pause distribution and modeling in quasi-spontaneous speech. In Proceedings of the International Conference of Phonetic Sciences, San Francisco, USA, August 1999.
15. Popescu-Belis, Andrei, Alexander Clark, Maria Georgescul, Denis Lalanne & Sandrine Zufferey (2004). Shallow discourse processing using machine learning algorithms (or not). In S. Bengio & H. Bourlard (Eds.), Machine Learning for Multimodal Interaction, Vol. 3361, Springer Lecture Series in Computer Science, pp. 277-290. Springer.
16. Shriberg, Elizabeth Ellen (1994). Preliminaries to a Theory of Speech Disfluencies, (Ph. D. thesis). University of California at Berkeley.
17. Siegel, Sidney & N. John Castellan (1988). Nonparametric Statistics for the Behavioral Sciences (2nd ed.). New York: McGraw-Hill.
18. Snover, Matthew, Bonnie Dorr & Richard Schwartz (2004). A lexically-driven algorithm for disfluency detection. In Proceedings of the Human Language Technolgy Conference of the North American Chapter of the Association for Computational Linguistics, Boston, Mass., 2-7 May, 2004, pp. 157-160.
19. Stouten, Frederik & Jean-Pierre Martens (2004). Coping with disfluencies in spontaneous speech recognition. In Proceedings of the International Conference on Spoken Language Processing, Vol. 2, pp. 1513-1516. Jeju Island Korea.
20. Teufel, Simone & Marc Moens (2002). Summarizing scientific articles: Experiments with relevance and rhetorical status. Computational Linguistics, 28(4):409-445.
21. Zechner, Klaus (2001). Automatic Summarization of Spoken Dialogues in Unrestricted Domains, (Ph. D. thesis). Language Technology Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, USA.