THAIWRITTENNET: THAI HANDWRITTEN SCRIPT RECOGNITION USING DEEP NEURAL NETWORKS

Abstract

Thai is a non-tonal language usage for 70 million speakers in Thailand. A variety of Thai handwrit-ten styles has been a challenge in handwriting recognition. In this paper, we propose a novel “ThaiWrittenNet” based on Convolutional Neural Network (ConvNet or CNN) with a cutout to identify the handwritten recognitions. Deep Belief Network (DBN) is also combined with Con-vNet to reduce network complexity. From the results, ThaiWrittenNet outperforms the flat Con-vNet and other handcrafted features with traditional machine learning algorithms. It appears that DBN helps ConvNet to improve the accuracy of Thai-handwritten recognition.