In this paper we describe our reproduction study of the human evaluation of text simplic- ity reported by Nisioi et al. (2017). The work was carried out as part of the ReproGen Shared Task 2022 on Reproducibility of Evaluations in NLG. Our aim was to repeat the evaluation of simplicity for nine automatic text simplification systems with a different set of evaluators. We describe our experimental design together with the known aspects of the original experimental design and present the results from both studies. Pearson correlation between the original and reproduction scores is moderate to high (0.776). Inter-annotator agreement in the reproduction study is lower (0.40) than in the original study (0.66). We discuss challenges arising from t...
Many texts we encounter in our everyday lives are lexically and syntactically very complex. This m...
Text simplification involves replacing or rephrasing (sections of) a document while minimizing meani...
Current Automatic Text Simplification (TS) work relies on sequence-to-sequence neural models that le...
In this paper we describe our reproduction study of the human evaluation of text simplic- ity report...
Text Simplification (TS) aims to reduce the linguistic complexity of content to make it easier to un...
In order to simplify sentences, several rewriting operations can be performed such as replacing comp...
There are rich opportunities to reduce the language complexity of professional content (either human...
Research in Text Simplification (TS) has relied mostly on the Wikipedia-based datasets and the SARI ...
While there is a vast amount of text written about nearly any topic, this is often difficult for som...
Automatic evaluation remains an open research question in Natural Language Generation. In the contex...
International audienceThe evaluation of text simplification (TS) systems remains an open challenge. ...
A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for...
This study explores the possibility of re-placing the costly and time-consuming human evaluation of ...
The quality of the output generated by automatic Text Simplification (TS) systems is traditionally a...
We propose a new method for evaluating the readability of simplified sentences through pair-wise ran...
Many texts we encounter in our everyday lives are lexically and syntactically very complex. This m...
Text simplification involves replacing or rephrasing (sections of) a document while minimizing meani...
Current Automatic Text Simplification (TS) work relies on sequence-to-sequence neural models that le...
In this paper we describe our reproduction study of the human evaluation of text simplic- ity report...
Text Simplification (TS) aims to reduce the linguistic complexity of content to make it easier to un...
In order to simplify sentences, several rewriting operations can be performed such as replacing comp...
There are rich opportunities to reduce the language complexity of professional content (either human...
Research in Text Simplification (TS) has relied mostly on the Wikipedia-based datasets and the SARI ...
While there is a vast amount of text written about nearly any topic, this is often difficult for som...
Automatic evaluation remains an open research question in Natural Language Generation. In the contex...
International audienceThe evaluation of text simplification (TS) systems remains an open challenge. ...
A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for...
This study explores the possibility of re-placing the costly and time-consuming human evaluation of ...
The quality of the output generated by automatic Text Simplification (TS) systems is traditionally a...
We propose a new method for evaluating the readability of simplified sentences through pair-wise ran...
Many texts we encounter in our everyday lives are lexically and syntactically very complex. This m...
Text simplification involves replacing or rephrasing (sections of) a document while minimizing meani...
Current Automatic Text Simplification (TS) work relies on sequence-to-sequence neural models that le...