Spelling Correction
26 papers with code • 0 benchmarks • 2 datasets
Spelling correction is the task of detecting and correcting spelling mistakes.
Benchmarks
These leaderboards are used to track progress in Spelling Correction
Most implemented papers
An Actor-Critic Algorithm for Sequence Prediction
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
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
There are a lot of noise texts surrounding a person in modern life.
Tokenization Repair in the Presence of Spelling Errors
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
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
We report very good translation results, especially when using neural MT for Chinese-to-Japanese translation.
Systematically Adapting Machine Translation for Grammatical Error Correction
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
We present an unsupervised context-sensitive spelling correction method for clinical free-text that uses word and character n-gram embeddings.