Recognising cursive Arabic text using a speech recognition system
M. S. Khorsheed · 2006
Abstract—This paper presents a system to recognise cursive Arabic typewritten text. The system is built using the Hidden Markov Model Toolkit (HTK) which is a portable toolkit for speech recognition system. The proposed system decomposes the page into its text lines and then extracts a set of simple statistical features from small overlapped windows running through each text line. The feature vector sequence is injected to the global model for training and recognition purposes. A data corpus which includes Arabic text from two computer-generated fonts is used to assess the performance of the proposed system.