A comparative study of probabilistic ranking models for Chinese spoken document summarization

ACM Transactions on Asian Language Information Processing

Volumn 8, Issue 1, 2009, Pages

  Lin, Shih Hsiang ^a   Chen, Berlin ^a   Wang, Hsin Min ^b  

^a NATIONAL TAIWAN NORMAL UNIVERSITY   (Taiwan)

^b INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

Author keywords

Extractive summarization; Probabilistic ranking models; Relevance information; Spoken document summarization

Indexed keywords

BROADCAST NEWS; COMPARATIVE STUDIES; DOCUMENT SUMMARIZATION; EXTRACTIVE SUMMARIZATION; MANDARIN CHINESE; PROBABILISTIC RANKING; PROBABILISTIC RANKING MODELS; RELEVANCE INFORMATION; RELIABLE DOCUMENTS; SPOKEN DOCUMENT; SPOKEN DOCUMENT SUMMARIZATION; SUPERVISED CLASSIFICATION; TRAINING DATA;

DATA REDUCTION;

INFORMATION RETRIEVAL SYSTEMS;

EID: 67149093166     PISSN: 15300226     EISSN: 15583430     Source Type: Journal    
DOI: 10.1145/1482343.1482346     Document Type: Article

References (53)

1. AUBERT, X. L. 2002. An overview of decoding techniques for large vocabulary continuous speech recognition. Comput. Speech Lang. 16, 1, 89-114.
2. BAEZA-YATES, R. AND RIBEIRO-NETO, B. 1999. Modern information retrieval. Addison-Wesley.
3. BAXENDALE, P. B. 1958. Machine-made index for technical literature - An experiment. IBM J. Res. Dev. 2, 4, 354-361.
4. BELLEGARDA, J. R. 2004. Statistical language model adaptation: Review and perspectives. Speech Comm. 42, 1, 93-108.
5. BLEI, D. M., NG, A. Y., AND JORDAN, M. I. 2003. Latent Dirichlet Allocation. J. Mach. Learn. Res. 3, 993-1022.
6. CHANG, C. C. AND LIN, C. J. 2001. LIBSVM: A library for support vector machines. Retrieved from http://www.csie.ntu.edu.tw/~cjlin/libsvm.
7. CHELBA, C., HAZEN, T. J., AND SARAÇLAR, M. 2008. Retrieval and browsing of spoken content. IEEE Signal Process. Mag. 25, 3, 39-49. (Pubitemid 351695639)
8. CHEN, B., KUO, J. W., AND TSAI, W. H. 2004. Lightly supervised and data-driven approaches to mandarin broadcast news transcription. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'04), 777-780.
9. CHEN, B. 2009. Word topic models for spoken document retrieval and transcription. ACM Trans. Asian Lang. Inform. Process. 8, 1.
10. CHEN, B. 2006. Exploring the use of latent topical information for statistical Chinese spoken document retrieval. Pattern Recogn. Lett. 27, 1, 9-18.
11. CHEN, B. AND CHEN, Y. T. 2008. Extractive spoken document summarization for information retrieval. Pattern Recogn. Lett. 29, 4, 426-437.
12. CHEN, B., YEH, Y. M., HUANG, Y. M., AND CHEN, Y. T. 2006a. Chinese spoken document summarization using probabilistic latent topical information. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'06), 969-972.
13. CHEN, Y. T., YU, S., WANG, H. M., AND CHEN, B. 2006b. Extractive Chinese spoken document summarization using probabilistic ranking models. In Proceedings of the International Symposium on Chinese Spoken Language Processing (ISCSLP'06), 660-671.
14. CHRISTENSEN, H., GOTOH, Y., AND RENALS, S. 2008. A cascaded broadcast news highlighter. IEEE Trans. Audio Speech Lang. Process. 16, 1, 151-161.
15. CONROY, J. M. AND O'LEARY, D. P. 2001. Text summarization via hidden markov models. In Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR'01), 406-407. (Pubitemid 32951104)
16. CROFT, W B. AND LAFFERTY, J. EDS. 2003. Language Modeling for Information Retrieval. Kluwer-Academic Publishers.
17. DEMPSTER, A. P., LAIRD, N. M., AND RUBIN, D. B. 1977. Maximum likelihood from incomplete data via the EM algorithm. J. Royal Stat. Soc. Series B 39, 1, 1-38.
18. DUDA, R. O., HART, P. E., AND STORK, D. G. 2001. Pattern Classification. Wiley-Interscience.
19. FURUI, S., KIKUCHI, T., SHINNAKA, Y., AND HORI, C. 2004. Speech-to-text and speech-to-speech summarization of spontaneous speech. IEEE Trans. Speech Audio Process. 12, 4, 401-408.
20. GILBERT, M. AND FENG, J. 2008. Speech and language processing over the Web. IEEE Signal Process. Mag. 25, 3, 42-60.
21. GONG, Y. AND LIU, X. 2001. Generic text summarization using relevance measure and latent semantic analysis. In Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR'01), 19-25. (Pubitemid 32951051)
22. HIROHATA, M., SHINNAKA, Y., IWANO, K., AND FURUI, S. 2005. Sentence extraction-based presentation summarization techniques and evaluation metrics. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'05), 1065-1068.
23. HOFMANN, T. 2001. Unsupervised learning by probabilistic latent semantic analysis. Mach. Learn. 42, 177-196.
24. KOUMPIS, K. AND RENALSS. 2005. Automatic summarization of voicemail messages using lexical and prosodic features. ACM Trans. Speech Lang. Process. 2, 1, 1-24.
25. KUMAR, N. 1997. Investigation of silicon-auditory models and generalization of linear discriminant analysis for improved speech recognition. Ph.D. Thesis. John Hopkins University.
26. KUPIEC, J., PEDERSEN, J., AND CHEN, F. 1999. Atrainable document summarizer. In Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR'99), 68-73.
27. LAFFERTY, J., MCCALLUM, A., AND PEREIRA, F. 2001. Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In Proceedings of the International Conference on Machine Learning (ICML'01), 282-289.
28. LEE, L. S. AND CHEN, B. 2005. Spoken document understanding and organization. IEEE Signal Process. Mag. 22, 5, 42-60. (Pubitemid 41488520)
29. LIN, C. Y. 2003. ROUGE: Recall-oriented understudy for gisting evaluation. Retrieved from http://www.isi.edu/-cyl/ROUGE/.
30. LIN, H. T., LIN, C. J., AND WENG, R. C. 2003. A note on Platt's probabilistic outputs for support vector machines. Mach. Learn. 68, 3, 267-276.
31. LIU, S. H., CHU, F. H., LIN, S. H., LEE, H. S., AND CHEN, B. 2007. Training data selection for improving discriminative training of acoustic models. In Proceedings of the IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU'07), 284-289.
32. LIU, Y. AND XIE, S. 2008. Impact of automatic sentence segmentation on meeting summarization. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'08), 5009-5012.
33. MASKEY, S. AND HIRSCHBERG, J. 2005. Comparing lexical, acoustic/prosodic, structural and discourse features for speech summarization. In Proceedings of the European Conference Speech Communication and Technology (EUROSPEECH'05), 621-624. (Pubitemid 43908139)
34. MASKEY, S. AND HIRSCHBERG, J. 2006. Summarizing speech without text using hidden markov models. In Proceedings of Human Language Technology Conference - North American Chapter of the Association for Computational Linguistics Annual Meeting (HLT-NAACL'06).
35. MURRAY, G., RENALS, S., AND CARLETTA, J. 2005. Extractive summarization of meeting recordings. In Proceedings of the European Conference on Speech Communication and Technology (EUROSPEECH'05), 593-596. (Pubitemid 43908132)
36. NOMOTO, T. AND MATSUMOTO, Y. 2001. A new approach to unsupervised text summarization. In Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR'99), 26-34. (Pubitemid 32951052)
37. ORTMANNS, S., NEY, H., AND AUBERT, X. 1997. A word graph algorithm for large vocabulary continuous speech recognition. Comput. Speech Lang. 11, 1, 43-72. (Pubitemid 127375893)
38. PAICE, C. D. 1990. Constructing literature abstracts by computer: Techniques and prospects. Inform. Process. Manag. 26, 1, 171-186.
39. POVEY, D. AND WOODLAND, P. C. 2002. Minimum phone error and I-smoothing for improved discriminative training. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'02), 105-108.
40. SAON, G., PADMANABHAN, M., GOPINATH, R., AND CHEN, S. 2000. Maximum likelihood discriminant feature spaces. In Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'00), 1129-1132.
41. SHEN, D., SUN, J. T., LI, H., YANG, Q., AND CHEN, Z. 2007. Document summarization using conditional random fields. In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'07), 2862-2867.
42. SJÖLANDER, K. 2001. Snack Sound Toolkit. Retrieved from http://www.speech.kth.se/snack/.
43. STOLCKE, A. 2005. SRI Language Modeling Toolkit. http://www.speech.sri. com/projects/srilm/.
44. VAPNIK, V. N. 1998. Statistical Learning Theory. Wiley-Interscience.
45. WANG, H. M., CHEN, B., KUO, J. W., AND CHENG, S. S. 2005. MATBN: A Mandarin Chinese broadcast news corpus. Int. J. Comput. Ling. Chinese Lang. Process. 10, 2, 219-236.
46. WEI, X. AND CROFT, W B. 2006. LDA-based document models for ad-hoc retrieval. In Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR'06), 178-185.
47. WESSEL, F., SCHLUTER, R., MACHEREY, K. AND NEY, H. 2001. Confidence measures for large vocabulary continuous speech recognition. IEEE Trans. Speech Audio Process. 9, 3, 288-298. (Pubitemid 32286598)
48. WITBROCK, M. AND MITTAL, V. 1999. Ultra summarization: A statistical approach to generating highly condensed non-extractive summaries. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'99), 315-316.
49. WONG, K. F., WU, M., AND LI, W. 2008. Extractive summarization using supervised and semi-supervised learning. In Proceedings of the International Conference on Computational Linguistics (COLING'08), 985-992.
50. ZHAI, C. AND LAFFERTY, J. 2001. A study of smoothing methods for language models applied to ad hoc information retrieval. In Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR'01), 334-342. (Pubitemid 32957519)
51. ZHANG, J., CHAN, H. Y., FUNG, P., AND CAO, L. 2007. A comparative study on speech summarization of broadcast news and lecture speech. In Proceedings of the European Conference on Speech Communication and Technology (EUROSPEECH'07), 2781-2784.
52. ZHANG, J. AND FUNG, P. 2007. Speech summarization without lexical features for mandarin broadcast news. In Proceedings of Human Language Technology Conference - North American Chapter of the Association for Computational Linguistics Annual Meeting (HLT-NAACL'07), 213-216.
53. ZHU, X. 2005. Semi-supervised learning literature survey. Tech. rep. Computer Sciences, University of Wisconsin-Madison.