A maximum entropy approach to Chinese pin yin-to-character conversion

Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

Volumn 4, Issue , 2006, Pages 2956-2959

  Wang, Xuan ^a,b   Li, Lu ^b   Yao, Lin ^b   Anwar, Waqas ^b  

^a IEEE   (China)

^b HARBIN INSTITUTE OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ENTROPY; FEATURE EXTRACTION; PROBLEM SOLVING;

CONVERSATION PERFORMANCE; HIT RATE; NON LOCAL INFORMATION;

CHARACTER RECOGNITION;

EID: 34548134108     PISSN: 1062922X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSMC.2006.384567     Document Type: Conference Paper

References (20)

1. Wang Xiaolong, Chen Qingcai, and Daniel S. Yeung, Mining Pinyin-to-Character Conversion Rules From Large-Scale Corpus: A Rough Set Approach, IEEE Trans. On Systems, Ma, and Cybernetics - Part B: Cybernetics, vol.34 No.2, pp 834-844
2. R. Kuhn and R. A. Mori, Cache-based natural language model for speech recognition, IEEE Trans. Patt. Anal. Mach. Intell. 12(6) (1990) 570-583.
3. K. F. Lee, H. W. Hon and R. Reddy, An overview of the sphinx speech recognition system, IEEE Trans. Acoust. Speech Sign. Process. 38(1) (1990) 35-45.
4. M. Ostendorf, V. V. Digalakis and O. A. Kimball, From HMM's to segment model: a unified view of stochastic modeling for speech recognition, IEEE Trans. Speech Audio Process. 4(5) (1996) 360-378.
5. Z. Chen and K.F. Lee, "A new statistical approach to Chinese Pinyin input," in ACL-2000, Hong Kong, 2000, pp.241-247.
6. X. Wang, D. Yeung, and X. Wang, "Chinese intelligent input method," in Proc. Int. Conf. Artificial Intelligence. Las Vegas, NV, 2000, pp. 1203-1208
7. J. Goodman, "A bit of progress in language modeling," Comput. Speech Lang., vol.15, pp. 403-434, 2001. M. Young, The Technical Writers Handbook. Mill Valley, CA: University Science, 1989.
8. H. Ney, U. Essen, and R. Kneser, "on structuring probabilistic dependences in stochastic language modeling," Compt. Speech Lang., vol. 8, pp. 1-38, 1994.
9. R. Rosenfeld, "A maximum entropy approach to adaptive statistical language modeling," Comput. Speech Lang., vol. 10, pp. 187-228, 1996.
10. B. Roark, "Probabilistic top-down parsing and language modeling," Computational Linguistics, vol. 27, no. 2, pp. 249-276, 2001.
11. C. Chelba and F. Jelinek, "Structured language modeling," Comput. Speech Lang., vol. 14, no. 4, pp. 283-332, 2001.
12. P. F. Brown, V. J. Della Pietra, P. V. deSouza, J. C. Lai, and R. L. Mercer, "Class-based n-gram models of natural language," Computational Linguistic, vol. 8, pp. 467-479, 1992.
13. T. R. Niesler and P. C. Woodland, "Variable-length category n-gram language models," Comput. Speech Lang., vol. 13 pp. 99-124, 1999
14. Fu, S. W. K., C. H. Lee and Orville L. C. 1996. A survey on Chinese Speech Recognition, Communications of COLIPS, 6(1):1-17.
15. G. W. Juette and L. E. Zeffanella, "Radio noise currents n short sections on bundle conductors (Presented Conference Paper style)," presented at the IEEE Summer power Meeting, Dallas, TX, June 22-27, 1990, Paper 90 SM 690-0 PWRS.
16. Lee, Y. S. 2003. Task adaptation in Stochastic Language Model for Chinese Honophone Disambiguation, ACM Transactions on Asian Language Information Processing, 2(1): 49-62.
17. E. T. Jaynes. Information theory and statistical mechanics. The Physical Review, 106:620-630, 1957.
18. E. T. Jaynes. Notes on present status and future prospects. Maximum Entropy and Bayesian Methods, pages 1-13, 1991.
19. Adam L. Berger, Stephen Della Pietra, and Vincent J. Della Pietra. A maximum entropy approach to natural language processing. Computational Linguistics, 22(1): 39-71, 1996.
20. Stephen Della Pietra, Vincent Della Pietra, Robert Mercer, and Salim Roukos. Adaptive language modeling using minimum discriminate estimation. In International Conference on Acoustics, Speech and Signal Processing, pages 633-636, San Francisco, march 1992.