Title :
Recognition of printed Devanagari text using BLSTM Neural Network
Author :
Sankaran, Naveen ; Jawahar, C.V.
Author_Institution :
Int. Inst. of Inf. Technol., Hyderabad, India
Abstract :
In this paper, we propose a recognition scheme for the Indian script of Devanagari. Recognition accuracy of Devanagari script is not yet comparable to its Roman counterparts. This is mainly due to the complexity of the script, writing style etc. Our solution uses a Recurrent Neural Network known as Bidirectional LongShort Term Memory (BLSTM). Our approach does not require word to character segmentation, which is one of the most common reason for high word error rate. We report a reduction of more than 20% in word error rate and over 9% reduction in character error rate while comparing with the best available OCR system.
Keywords :
natural language processing; optical character recognition; recurrent neural nets; text analysis; BLSTM neural network; Devanagari script recognition accuracy; Indian Devanagari script; OCR system; Roman counterparts; bidirectional long-short term memory; character segmentation; printed Devanagari text recognition; recurrent neural network; script complexity; word error rate; writing style; Accuracy; Character recognition; Degradation; Feature extraction; Logic gates; Neural networks; Optical character recognition software; BLSTM; Devanagari; OCR; Word recognition;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4