Detection and Interpretation of Opinion Expressions in Spoken Surveys

IEEE Transactions on Audio, Speech and Language Processing

Volumn 18, Issue 2, 2010, Pages 369-381

  Camelin, Nathalie ^a   Bechet, Frederic ^a   De Mori, Renato ^a   Damnati, Géraldine ^b  

^a UNIVERSITY OF AVIGNON   (France)

^b ORANGE LABS   (France)

Author keywords

Automatic detection of in domain speech data; automatic processing of telephone surveys; automatic speech recognition; spoken language understanding; spoken opinion analysis

Indexed keywords

EID: 85008544109     PISSN: 15587916     EISSN: 15587924     Source Type: Journal    
DOI: 10.1109/TASL.2009.2028918     Document Type: Article

References (35)

1. N. Camelin, F. Bechet, G. Damnati, and R. De Mori, “Automatic customer feedback processing: Alarm detection in open question spoken messages,” in Proc. Interspeech, Brisbane, Australia, 2008, pp. 475–478.
2. J. Wiebe, T. Wilson, and C. Cardie, “Annotating expressions of opinions and emotions in language,” Lang. Resources Eval. (Formerly Comput. Humanities), vol. 39, pp. 165–210, 2005.
3. T. Wilson, J. Wiebe, and P. Hoffmann, “Recognizing contextual polarity in phrase-level sentiment analysis,” in Proc. HLT/EMNLP, Vancouver, BC, Canada, 2005, pp. 347–354.
4. S.-M. Kim and E. Hovy, “Extracting opinions, opinion holders, and topics expressed in online news media text,” in Proce. Workshop on Sentiment and Subjectivity in Text, Sydney, Australia, Jul. 2006, pp. 1–8, Assoc. Comput. Linguist.
5. A.-M. Popescu and O. Etzioni, “Extracting product features and opinions from reviews,” in Proc. HLT/EMNLP, 2005, pp. 339–346.
6. S. Bethard, H. Yu, A. Thornton, V. Hatzivassiloglou, and D. Jurafsky, “Automatic extraction of opinion propositions and their holders,” in Proc. AAAI Spring Symp. Exploring Attitude and Affect in Text: Theories Applicat., 2004, pp. 22–24.
7. B. Pang, L. Lee, and S. Vaithyanathan, “Thumbs up?: Sentiment classification using machine learning techniques,” in Proc. ACL-02 Conf. EMNLP (EMNLP'02), Morristown, NJ, 2002, pp. 79–86, Assoc. for Comput. Linguist.
8. P. D. Turney, “Thumbs up or thumbs down?: Semantic orientation applied to unsupervised classification of reviews,” in Proc. ACL'02: 40th Annu. Meeting on ACL, Morristown, NJ, 2002, pp. 417–424, Assoc. for Comput. Linguist.
9. R. F. Bruce and J. M. Wiebe “Recognizing subjectivity: A case study in manual tagging,” Natural Lang. Eng., vol. 5, no. 2, pp. 187–205, 1999.
10. J. Wiebe, T. Wilson, and M. Bell, “Identifying collocations for recognizing opinions,” in Proc. ACL/EACL 2001 Workshop Collocation, 2001, pp. 24–31.
11. K. Dave, S. Lawrence, and D. M. Pennock, “Mining the peanut gallery: Opinion extraction and semantic classification of product reviews,” in Proc. 12th Int. Conf. World Wide Web WWW '03, New York, 2003, pp. 519–528, ACM Press.
12. M. Hu and B. Liu, “Mining and summarizing customer reviews,” in Proc. 10th ACM SIGKDD Int. Conf. Knowledge Discovery Data Mining KDD '04:, New York, 2004, pp. 168–177, ACM Press.
13. S.-M. Kim and E. Hovy, “Identifying opinion holders for question answering in opinion texts,” in Proc. AAAI-05 Workshop Question Answering in Restricted Domains, Pittsburgh, PA, 2005.
14. V. Stoyanov and C. Cardie, “Toward opinion summarization: Linking the sources,” in Proc. Workshop Sentiment and Subjectivity in Text, Sydney, Australia, Jul. 2006, pp. 9–14, Assoc. for Comput. Linguist.
15. J. M. Wiebe “Tracking point of view in narrative,” Comput. Linguist., vol. 20, no. 2, pp. 233–287, 1994.
16. S. M. Kim and E. Hovy, “Determining the sentiment of opinions,” in Proc. 20th Int. Conf. Comput. Linguist. COLING'04:, Morristown, NJ, 2004, pp. 1367–1373, Assoc. Comput. Linguist.
17. B. Pang and L. Lee, “A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts,” in Proc. Assoc. Comput. Linguist., 2004, pp. 271–278.
18. J. M. Wiebe, R. F. Bruce, and T. P. O'Hara, “Development and use of a gold-standard data set for subjectivity classifications,” in Proc. 37th Annu. Meeting Assoc. Comput. Linguist., Morristow, NJ, 1999, pp. 246–253, Assoc. Comput. Linguist.
19. H. Yu and V. Hatzivassiloglou, “Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences,” in Proc. 2003 Conf. EMNLP, Morristown, NJ, 2003, pp. 129–136, Assoc. Comput. Linguist.
20. E. Riloff and J. Wiebe, “Learning extraction patterns for subjective expressions,” in Proc. 2003 Conf. EMNLP, 2003, pp. 105–112.
21. T. Wilson, J. Wiebe, and R. Hwa, “Just how mad are you? Finding strong and weak opinion clauses,” in Proc. 19th National Conf. Artif. Intell., 2004, pp. 761–769.
22. B. Levin, English Verb Classes and Alternations: A Preliminary Investigation. Chicago, IL: Univ. of Chicago Press, 1993.
23. V. Hatzivassiloglou and K. R. McKeown, “Predicting the semantic orientation of adjectives,” in Proc. 8th Conf. Eur. Chapt. ACL, Morristown, NJ, 1997, pp. 174–181, Assoc. Comput. Linguist.
24. Y. Choi, C. Cardie, E. Riloff, and S. Patwardhann, “Identifying sources of opinions with conditional random fields and extraction patterns,” in Proc. HLT/EMNLP, Vancouver, BC, Canada, 2005, pp. 355–362.
25. C. M. Lee and S. Narayanan, “Toward detecting emotions in spoken dialogs,” IEEE Trans. Speech Audio Process., vol. 13, no. 2, pp. 293–303, Mar. 2005.
26. D. J. Litman, C. P. Rosé, K. Forbes-Riley, K. VanLehn, D. Bhembe, and S. Silliman, “Spoken versus typed human and computer dialogue tutoring,” Int. J. Artif. Intell. Education, vol. 16, no. 2, pp. 145–170, 2006.
27. D. Neiberg, K. Elenius, and K. Laskowski, “Emotion recognition in spontaneous speech using GMMs,” in Proc. 9th Int. Conf. Spoken Lang. Process. ISCA, 2006, pp. 809–812.
28. J. Liscombe, “Detecting emotion in speech: Experiments in three domains,” in Proc. 2006 Conf. North Amer. Chapt. Assoc. Comput. Linguist. Human Lang. Technol.: Companion Vol.: Doctoral Consortium, Morristown, NJ, 2006, pp. 231–234, Assoc. Comput. Linguist. Morristown.
29. N. Camelin, G. Damnati, F. Bechet, and R. De Mori, “Opinion mining in a telephone survey corpus,” in Proc. Int. Conf. Spoken Lang. Process., Pittsburg, PA, 2006, pp. 1041–1044.
30. J. Lafferty, A. Mccallum, and F. Pereira, “Conditional random fields: Probabilistic models for segmenting and labeling sequence data,” in Proc. 18th Int. Conf. Mach. Learn., San Francisco, CA, 2001, pp. 282–289, Morgan Kaufmann.
31. C. Raymond, F. Bechet, N. Camelin, R. De Mori, and G. Damnati, “Sequential decision strategies for machine interpretation of speech,” IEEE Trans. Speech Audio Process., vol. 15, no. 1, pp. 162–171, Jan. 2007.
32. R. E. Schapire and Y. Singer, “BoosTexter: A boosting-based system for text categorization,” Mach. Learn., vol. 39, pp. 135–168, 2000.
33. C. Whissell, “The distinct emotional flavor of Gnostic writings from the early Christian era,” Psychol. Rep., vol. 102, no. 1, pp. 213–34, 2008.
34. R. E. Schapire, M. Rochery, M. Rahim, and N. Gupta, “Boosting with prior knowledge for call classification,” IEEE Trans. Speech Audio Process., vol. 13, no. 1, pp. 174–181, Mar. 2005.
35. N. Camelin, R. De Mori, F. Bechet, and G. Damnati, “Error correction of proportions in spoken opinion surveys,” in Proc. Interspeech, Brighton, U.K., 2009.