In this paper, we describe a system for correcting grammatical errors in texts written by non-native English learners. In our approach, a given sentence is sent to a number of modules, each focuses on a specific error type. The modules apply different approaches tailored to different types of...
Grammatical Error Correction Grammatical Error Correction (GEC) is the task of correcting different kinds of errors in text such as spelling, punctuation, grammatical, and word choice errors. GEC is typically formulated as a sentence correction task. A GEC system takes a potentially erroneous sentence...
Grammatical Error Correction (GEC) is the task of correcting different kinds of errors in text such as spelling, punctuation, grammatical, and word choice errors. GEC is typically formulated as a sentence correction task. A GEC system takes a potentially erroneous sentence as input and is expected...
Google first announced grammar correction ina blog post in October, saying, "We are launching a grammar correction feature that is directly built into Gboard on Pixel 6 that works entirely on-device to preserve privacy, detecting and suggesting corrections for grammatical errors while the user is t...
Identification and Correction of Grammatical Errors in Ukrainian Texts Based on Machine Learning Technology A machine learning model for correcting errors in Ukrainian texts has been developed. It was established that the neural network has the ability to correct... V Lytvyn,P Pukach,MKN Vysotska ...
Grammatical error correction (GEC) systems strive to correct both global errors in word order and usage, and local errors in spelling and inflection. Further developing upon recent work on neural machine translation, we propose a new hybrid neural model with nested attention layers for GE...
The task not only includes the correction of grammatical errors, such as missing prepositions and mismatched subject–verb agreement, but also orthographic and semantic errors, such as misspellings and word choice errors, respectively. The field has seen significant progress in the last decade, ...
Synthetic data generation is widely known to boost the accuracy of neural grammatical error correction (GEC) systems, but existing methods often lack diversity or are too simplistic to generate the broad range of grammatical errors made by human writers. In this work, we use error type tags from...
Progress in neural grammatical error correction (GEC) is hindered by the lack of annotated training data. Sufficient amounts of high-quality manually annotated data are not available, so recent research has relied on generating synthetic data, pretraining on it, and then fine-tuning on real datas...
Incorrect:The hearing was planned for Monday, December 2, but not all of the witnesses could be available, so it was rescheduled for the following Friday. [There are no grammatical errors here, but the sprawling sentence does not communicate clearly and concisely.] Revised: ...