Nov 1, 2018 · We propose a nested recurrent neural network (nested RNN) model for English spelling error correction and generate pseudo data based on phonetic ...
A nested recurrent neural network model that fuses orthographic information and context as a whole and is trained in an end-to-end fashion and does not rely ...
We propose a nested recurrent neural network (nested RNN) model for English spelling error correction and generate pseudo data based on phonetic similarity ...
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We introduce NeuSpell, an open-source toolkit for spelling correction in English. Our toolkit comprises ten different models, and.
Spelling error correction using a nested rnn model and pseudo training data. ... Spelling error correction using a nested rnn model and pseudo training data.
We propose a nested recurrent neural network (nested RNN) model for English spelling error correction and generate pseudo data based on phonetic similarity to ...
To combat adversarial spelling mistakes, we propose placing a word recognition model in front of the downstream classifier. Our word.
The context-sensitive spelling error problem is solved using the deep learning method, which is not an existing statistical method, and the best correction ...
We introduce NeuSpell, an open-source toolkit for spelling correction in English. Our toolkit comprises ten different models, and benchmarks them on ...
This toolkit offers 3 kinds of noising strategies (identfied from existing literature) to generate synthetic parallel training data to train neural models for ...
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