Detecting Grammatical Errors in Machine Translation Output Using Dependency Parsing and Treebank Querying

Detecting English Grammatical Errors based on Machine Translation

Bangla Grammatical Error Detection Using T5 Transformer Model

This paper presents a method for detecting grammatical errors in Bangla using a Text-to-Text Transfer Transformer (T5) Language Model, using the small variant of BanglaT5, fine-tuned on a corpus of 9385 sentences where e…

A Syntax-Guided Grammatical Error Correction Model with Dependency Tree Correction

Grammatical Error Correction (GEC) is a task of detecting and correcting grammatical errors in sentences. Recently, neural machine translation systems have become popular approaches for this task. However, these methods …

Neural Machine Translation of Text from Non-Native Speakers

Neural Machine Translation (NMT) systems are known to degrade when confronted with noisy data, especially when the system is trained only on clean data. In this paper, we show that augmenting training data with sentences…

An Analysis of Source-Side Grammatical Errors in NMT

The quality of Neural Machine Translation (NMT) has been shown to significantly degrade when confronted with source-side noise. We present the first large-scale study of state-of-the-art English-to-German NMT on real gra…