Perceptual Quality Dimensions of Machine-Generated Text with a Focus on Machine Translation

被引：0
|
作者：
Macketanz, Vivien [1 ]
Naderi, Babak [2 ]
Schmidt, Steven [2 ]
Moeller, Sebastian [2 ]
机构：
[1] German Res Ctr AI, Kaiserslautern, Germany
[2] TU Berlin, Qual & Usabil Lab, Berlin, Germany
来源：
PROCEEDINGS OF THE 2ND WORKSHOP ON HUMAN EVALUATION OF NLP SYSTEMS (HUMEVAL 2022) | 2022年
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D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The quality of machine-generated text is a complex construct consisting of various aspects and dimensions. We present a study that aims to uncover relevant perceptual quality dimensions for one type of machine-generated text, that is, Machine Translation. We conducted a crowd-sourcing survey in the style of a Semantic Differential to collect attribute ratings for German MT outputs. An Exploratory Factor Analysis revealed the underlying perceptual dimensions. As a result, we extracted four factors that operate as relevant dimensions for the Quality of Experience of MT outputs: precision, complexity, grammaticality, and transparency.
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页码：24 / 31
页数：8
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