Integrated convolutional neural network (CNN) and deep bidirectional long short-term
memory (DBLSTM) based character models have achieved excellent recognition accuracies …

Recently, character model based on integrated convolutional neural network (CNN) and
deep bidirectional long short-term memory (DBLSTM) has achieved excellent performance …

Arabic handwriting recognition is considered among the most important and challenging
recognition research subjects due to the cursive nature of writing and the similarities …

Attention-based encoder-decoder approaches have shown promising results in scene text
recognition. In the literature, models with different encoders, decoders and attention …

Abstract Today's Arabic Handwriting recognition systems are able to recognize arbitrary
words over a large but finite vocabulary. Systems operating with a fixed vocabulary are …

Hybrid deep neural network hidden Markov models (DNN-HMM) have achieved impressive
results on large vocabulary continuous speech recognition (LVCSR) tasks. However, the …

Recently Adam has become a popular stochastic optimization method in deep learning
area. To parallelize Adam in a distributed system, synchronous stochastic gradient (SSG) …

In computational linguistics, language models are probabilistic models that predict the
likelihood of words occurring within specific sentences. They are key components of many …

Handwritten character recognition is a hot topic for research nowadays. If we can convert a
handwritten piece of paper into a text-searchable document using the Optical Character …

We present two weighted finite-state transducer (WFST) based decoders for handwriting
recognition. One decoder is a cloud-based solution that is both compact and efficient. The …