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Spelling Correction

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

Papers

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Showing 51–100 of 193 papers

TitleStatusHype
Persian Typographical Error Type Detection Using Deep Neural Networks on Algorithmically-Generated Misspellings—0
Beqi: Revitalize the Senegalese Wolof Language with a Robust Spelling Corrector—0
Cleansing Jewel: A Neural Spelling Correction Model Built On Google OCR-ed Tibetan Manuscripts—0
Improving Contextual Spelling Correction by External Acoustics Attention and Semantic Aware Data Augmentation—0
Correcting Real-Word Spelling Errors: A New Hybrid Approach—0
Real-Word Error Correction with Trigrams: Correcting Multiple Errors in a Sentence—0
Inducing Character-level Structure in Subword-based Language Models with Type-level Interchange Intervention TrainingCode0
DiaCorrect: End-to-end error correction for speaker diarizationCode0
Look Ma, Only 400 Samples! Revisiting the Effectiveness of Automatic N-Gram Rule Generation for Spelling Normalization in FilipinoCode0
BSpell: A CNN-Blended BERT Based Bangla Spell CheckerCode0
ABB-BERT: A BERT model for disambiguating abbreviations and contractionsCode0
English Language Spelling Correction as an Information Retrieval Task Using Wikipedia Search Statistics—0
Spelling Correction using Phonetics in E-commerce Search—0
MDCSpell: A Multi-task Detector-Corrector Framework for Chinese Spelling Correction—0
A New String Edit Distance and Applications—0
Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition SystemsCode0
Inkorrect: Online Handwriting Spelling Correction—0
Using Random Perturbations to Mitigate Adversarial Attacks on Sentiment Analysis Models—0
The Influence of Regional Pronunciation Variation on Children’s Spelling and the Potential Benefits of Accent Adapted Spellcheckers—0
VSEC: Transformer-based Model for Vietnamese Spelling Correction—0
Structured abbreviation expansion in context—0
Spelling Correction for Russian: A Comparative Study of Datasets and Methods—0
A Light-weight contextual spelling correction model for customizing transducer-based speech recognition systems—0
Correcting Arabic Soft Spelling Mistakes using BiLSTM-based Machine Learning—0
BERT-Defense: A Probabilistic Model Based on BERT to Combat Cognitively Inspired Orthographic Adversarial AttacksCode0
Spelling Correction with Denoising Transformer—0
Similarity-Based Unsupervised Spelling Correction Using BioWordVec: Development and Usability Study of Bacterial Culture and Antimicrobial Susceptibility ReportsCode0
Spell Correction for Azerbaijani Language using Deep Neural Networks—0
Misspelling Correction with Pre-trained Contextual Language Model—0
Vartani Spellcheck -- Automatic Context-Sensitive Spelling Correction of OCR-generated Hindi Text Using BERT and Levenshtein Distance—0
Comparison of Interactive Knowledge Base Spelling Correction Models for Low-Resource Languages—0
Disambiguating Confusion Sets as an Aid for Dyslexic Spelling—0
A Spelling Correction Corpus for Multiple Arabic Dialects—0
An In-Depth Comparison of 14 Spelling Correction Tools on a Common Benchmark—0
Automated Spelling Correction for Clinical Text Mining in Russian—0
A Financial Service Chatbot based on Deep Bidirectional Transformers—0
Neural Chinese Word Segmentation as Sequence to Sequence TranslationCode0
GitHub Typo Corpus: A Large-Scale Multilingual Dataset of Misspellings and Grammatical ErrorsCode0
Normalising Non-standardised Orthography in Algerian Code-switched User-generated Data—0
Sequence to Sequence Convolutional Neural Network for Automatic Spelling Correction—0
Algorithms for certain classes of Tamil Spelling correction—0
The Impact of Spelling Correction and Task Context on Short Answer Assessment for Intelligent Tutoring Systems—0
A Benchmark Corpus of English Misspellings and a Minimally-supervised Model for Spelling CorrectionCode0
Lexical Normalization of User-Generated Medical Text—0
How to account for mispellings: Quantifying the benefit of character representations in neural content scoring models—0
Ma copie adore le v\'elo : analyse des besoins r\'eels en correction orthographique sur un corpus de dict\'ees d'enfants (A corpus analysis to define the needs of dyslexic children in terms of spelling correction)—0
Robust to Noise Models in Natural Language Processing TasksCode0
Automatic Spelling Correction with Transformer for CTC-based End-to-End Speech Recognition—0
A spelling correction model for end-to-end speech recognition—0
Context-Sensitive Malicious Spelling Error Correction—0
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