Skip to main content
SpringerLink
Log in

Approach to the correlation discovery of Chinese linguistic parameters based on Bayesian method

  • Correspondence
  • Published:
Journal of Computer Science and Technology Aims and scope Submit manuscript

Abstract

Bayesian approach is an important method in statistics. The Bayesian belief network is a powerful knowledge representation and reasoning tool under the conditions of uncertainty. It is a graphics model that encodes probabilistic relationships among variables of interest. In this paper, an approach to Bayesian network construction is given for discovering the Chinese linguistic parameter relationship in the corpus.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Karaali Oet al. Text-to-speech conversion with neural networks: A recurrent TDNN approach. InProc. 5th European Conference on Speech Communication and Technology, Rhodes, Greece, September 22–25, 1997, pp.561–564.

  2. David Heckerman. Bayesian networks for data mining.Data Mining and Knowledge Discovery, 1997, 1: 79–119.

    Article  Google Scholar 

  3. Cheng J, Bell D A, Liu W. An algorithm for Bayesian belief network construction form data. InProc. 6th International Workshop on Artificial Intelligence and Statistics, Florida, USA, January 4–7, 1997.

  4. Wang Wei, Chen Enhong, Wang Xufa. Based on Bayesian approach for data mining.Mini-Micro Systems, 2000, 21(7): 703–705.

    Google Scholar 

  5. Wang wei, Cai Lianhong. Study of determining Bayesian network topology structures.Mini-Micro System, 2002, 23(4): 435–437.

    Google Scholar 

  6. Tao Jianhua, Cai Lianhong. A neural-network-based prosodic model of Mandarin TTS system.Journal of Acoustics, 2001, 26(1): 67–72.

    Google Scholar 

  7. David Heckerman, Christopher Meek, Gregory Cooper. A Bayesian Approach to Causal Discovery, Technical Report MSR-TR-97-05.

  8. Gregory F Cooper, Edward Herskovits. A Bayesian method for the induction of probabilistic networks from data.Marchine Learning, 1992, 9: 309–347.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, 100084, Beijing, P.R. China

    Wang Wei & Cai LianHong

Authors
  1. Wang Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cai LianHong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wang Wei.

Additional information

Supported by the National Natural Science Foundation of China (Grant No.69875008).

WANG Wei was born in 1973. He received the B.S. and M.S. degrees in electronic engineering and information science from Anhui University in 1995 and 1998 respectively, and the Ph.D. degree from the Department of Computer Science and Technology, University of Science and Technology of China in 2000. He is now a postdoctoral researcher at Tsinghua University. His research areas include multimedia information processing, data mining and machine learning.

CAI LianHong was born is 1945. She graduated from the Department of Automatic Control Engineering, Tsinghua University in 1970. She is now a professor at the Department of Computer Science and Technology, Tsinghua University. Her current research interests include speech synthesis, multimedia information processing.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, W., Cai, L. Approach to the correlation discovery of Chinese linguistic parameters based on Bayesian method. J. Comput. Sci. & Technol. 18, 97–101 (2003). https://doi.org/10.1007/BF02946656

Download citation

  • Received:

  • Revised:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02946656

Keywords

Search

Navigation