Grammatical error correction: A survey of the state of the art
Abstract Grammatical Error Correction (GEC) is the task of automatically detecting and
correcting errors in text. The task not only includes the correction of grammatical errors, such …
correcting errors in text. The task not only includes the correction of grammatical errors, such …
A comprehensive survey of grammatical error correction
Grammatical error correction (GEC) is an important application aspect of natural language
processing techniques, and GEC system is a kind of very important intelligent system that …
processing techniques, and GEC system is a kind of very important intelligent system that …
[HTML][HTML] Earthquake transformer—an attentive deep-learning model for simultaneous earthquake detection and phase picking
Earthquake signal detection and seismic phase picking are challenging tasks in the
processing of noisy data and the monitoring of microearthquakes. Here we present a global …
processing of noisy data and the monitoring of microearthquakes. Here we present a global …
An introductory survey on attention mechanisms in NLP problems
D Hu - Intelligent Systems and Applications: Proceedings of …, 2020 - Springer
First derived from human intuition, later adapted to machine translation for automatic token
alignment, attention mechanism, a simple method that can be used for encoding sequence …
alignment, attention mechanism, a simple method that can be used for encoding sequence …
Improving grammatical error correction via pre-training a copy-augmented architecture with unlabeled data
Neural machine translation systems have become state-of-the-art approaches for
Grammatical Error Correction (GEC) task. In this paper, we propose a copy-augmented …
Grammatical Error Correction (GEC) task. In this paper, we propose a copy-augmented …
PLOME: Pre-training with misspelled knowledge for Chinese spelling correction
S Liu, T Yang, T Yue, F Zhang… - Proceedings of the 59th …, 2021 - aclanthology.org
Chinese spelling correction (CSC) is a task to detect and correct spelling errors in texts. CSC
is essentially a linguistic problem, thus the ability of language understanding is crucial to this …
is essentially a linguistic problem, thus the ability of language understanding is crucial to this …
A multilayer convolutional encoder-decoder neural network for grammatical error correction
S Chollampatt, HT Ng - Proceedings of the AAAI conference on artificial …, 2018 - ojs.aaai.org
We improve automatic correction of grammatical, orthographic, and collocation errors in text
using a multilayer convolutional encoder-decoder neural network. The network is initialized …
using a multilayer convolutional encoder-decoder neural network. The network is initialized …
An empirical study of incorporating pseudo data into grammatical error correction
The incorporation of pseudo data in the training of grammatical error correction models has
been one of the main factors in improving the performance of such models. However …
been one of the main factors in improving the performance of such models. However …
Parallel iterative edit models for local sequence transduction
We present a Parallel Iterative Edit (PIE) model for the problem of local sequence
transduction arising in tasks like Grammatical error correction (GEC). Recent approaches …
transduction arising in tasks like Grammatical error correction (GEC). Recent approaches …
Approaching neural grammatical error correction as a low-resource machine translation task
Previously, neural methods in grammatical error correction (GEC) did not reach state-of-the-
art results compared to phrase-based statistical machine translation (SMT) baselines. We …
art results compared to phrase-based statistical machine translation (SMT) baselines. We …