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Using ASR methods for OCR
, Article 15th IAPR International Conference on Document Analysis and Recognition, ICDAR 2019, 20 September 2019 through 25 September 2019 ; 2019 , Pages 663-668 ; 15205363 (ISSN); 9781728128610 (ISBN) ; Garcia, P ; Watanabe, S ; Manohar, V ; Shao, Y ; Khudanpur, S ; Chang, C. C ; Rekabdar, B ; Babaali, B ; Povey, D ; Etter, D ; Raj, D ; Hadian, H ; Trmal, J ; Sharif University of Technology
IEEE Computer Society
2019
Abstract
Hybrid deep neural network hidden Markov models (DNN-HMM) have achieved impressive results on large vocabulary continuous speech recognition (LVCSR) tasks. However, the recent approaches using DNN-HMM models are not explored much for text recognition. Inspired by the current work in automatic speech recognition (ASR) and machine translation, we present an open vocabulary sub-word text recognition system. The sub-word lexicon and sub-word language model (LM) helps in overcoming the challenge of recognizing out of vocabulary (OOV) words, and a time delay neural network (TDNN) and convolution neural network (CNN) based DNN-HMM optical model (OM) efficiently models the sequence dependency in the...