ISCA Archive ICSLP 1994
ISCA Archive ICSLP 1994

A study on the simulated annealing of self organized map algorithm for Korean phoneme recognition

Myung-Kwang Kong, Seong-Kwon Lee, Soon-Hyob Kim

In this paper, we describe the new unsupervised learning algorithm, SASOM(Simulated Annealing Self Organized Map). It can solve the defects of the conventional SOM(Self-Organized Map) that the state of network can't converge to the minimum point. The proposed algorithm uses the object function which can evaluate the state of network in learning and adjusts the learning rate flexibly according to the evaluation of the object function. We implement the simulated annealing which is applied to the conventional network using the object function and the learning rate. Finally, the proposed algorithm can make the state of network converged to the global minimum. Using the two-dimensional input vectors with uniform distribution, we graphically compared the ordering ability of SOM with that of SASOM. We carried out the recognition on the new algorithm for all Korean phonemes and some continuous speech.


Cite as: Kong, M.-K., Lee, S.-K., Kim, S.-H. (1994) A study on the simulated annealing of self organized map algorithm for Korean phoneme recognition. Proc. 3rd International Conference on Spoken Language Processing (ICSLP 1994), 471-474

@inproceedings{kong94_icslp,
  author={Myung-Kwang Kong and Seong-Kwon Lee and Soon-Hyob Kim},
  title={{A study on the simulated annealing of self organized map algorithm for Korean phoneme recognition}},
  year=1994,
  booktitle={Proc. 3rd International Conference on Spoken Language Processing (ICSLP 1994)},
  pages={471--474}
}