automatic post-editing

Giving the Old a Fresh Spin: Quality Estimation-Assisted Constrained Decoding for Automatic Post-Editing

Automatic Post-Editing (APE) systems often struggle with over-correction, where unnecessary modifications are made to a translation, diverging from the principle of minimal editing. In this paper, we propose a novel technique to mitigate …

Refer to the Reference: Reference-focused Synthetic Automatic Post-Editing Data Generation

Together We Can: Multilingual Automatic Post-Editing for Low-Resource Languages

This exploratory study investigates the potential of multilingual Automatic Post-Editing (APE) systems to enhance the quality of machine translations for low-resource Indo-Aryan languages. Focusing on two closely related language pairs, …

APE-then-QE: Correcting then Filtering Pseudo Parallel Corpora for MT Training Data Creation

Automatic Post-Editing (APE) is the task of automatically identifying and correcting errors in the Machine Translation (MT) outputs. We propose a repair-filter-use methodology that uses an APE system to correct errors on the target side of the MT …

Findings of the WMT 2023 Shared Task on Automatic Post-Editing

We present the results from the 9th round of the WMT shared task on MT Automatic Post-Editing, which consists of automatically correcting the output of a “black-box” machine translation system by learning from human corrections. Like last year, the …

Quality Estimation-Assisted Automatic Post-Editing

Automatic Post-Editing (APE) systems are prone to over-correction of the Machine Translation (MT) outputs. While Word-level Quality Estimation (QE) system can provide a way to curtail the over-correction, a significant performance gain has not been …

Findings of the WMT 2022 Shared Task on Automatic Post-Editing

We present the results from the 8th round of the WMT shared task on MT Automatic Post-Editing, which consists in automatically correcting the output of a 'black-box' machine translation system by learning from human corrections. This year, the task …