HMM topology selection for on-line Thai handwriting recognition

Siriboon, K.; Jirayusakul, A.; Kruatrachue, B.

doi:10.1109/CW.2002.1180872

HMM topology selection for on-line Thai handwriting recognition

Author(s)

Siriboon, K.

Jirayusakul, A.

Kruatrachue, B.

Date Issued

January 1, 2002

Type

Conference Paper

DOI

10.1109/CW.2002.1180872

Abstract

Researchers have extensively applied hidden Markov models (HMM) to handwriting recognition in English, Chinese, and other languages. Most researchers have used left-right topology for handwriting and speech recognition. This research studied the effect of HMM topology on isolated online Thai handwriting recognition. The left-right, fully connected and proposed topologies (left-right-left) were compared. The number of states of a character HMM for each topology was varied from 15 to 35 nodes and the one with the best training observations probability was selected. The feature used was chain code-like with modifications to represent original quadrant position. The recognition results showed that the proposed topology increases the recognition rate compared to the most widely used left-right topology.

Citation

Proceedings 1st International Symposium on Cyber Worlds Cw 2002, 142-145, 2002