Spelling Correction

26 papers with code • 0 benchmarks • 2 datasets

Spelling correction is the task of detecting and correcting spelling mistakes.

Most implemented papers

An Actor-Critic Algorithm for Sequence Prediction

rizar/actor-critic-public 24 Jul 2016

We present an approach to training neural networks to generate sequences using actor-critic methods from reinforcement learning (RL).

MoNoise: Modeling Noise Using a Modular Normalization System

robvanderg/monoise 10 Oct 2017

We show that MoNoise beats the state-of-the-art on different normalization benchmarks for English and Dutch, which all define the task of normalization slightly different.

Robust to Noise Models in Natural Language Processing Tasks

madrugado/robust-w2v ACL 2019

There are a lot of noise texts surrounding a person in modern life.

Tokenization Repair in the Presence of Spelling Errors

ad-freiburg/tokenization-repair CoNLL (EMNLP) 2021

We identify three key ingredients of high-quality tokenization repair, all missing from previous work: deep language models with a bidirectional component, training the models on text with spelling errors, and making use of the space information already present.

Robsut Wrod Reocginiton via semi-Character Recurrent Neural Network

simonroquette/CORAP 7 Aug 2016

Inspired by the findings from the Cmabrigde Uinervtisy effect, we propose a word recognition model based on a semi-character level recurrent neural network (scRNN).

Kyoto University Participation to WAT 2016

fabiencro/knmt WS 2016

We report very good translation results, especially when using neural MT for Chinese-to-Japanese translation.

Systematically Adapting Machine Translation for Grammatical Error Correction

cnap/smt-for-gec WS 2017

Our model rivals the current state of the art using a fraction of the training data.

Unsupervised Context-Sensitive Spelling Correction of English and Dutch Clinical Free-Text with Word and Character N-Gram Embeddings

clips/clinspell 19 Oct 2017

We present an unsupervised context-sensitive spelling correction method for clinical free-text that uses word and character n-gram embeddings.