Perceptual Quality Dimensions of Machine-Generated Text with a Focus on Machine Translation
Vivien Macketanz, Babak Naderi, Steven P. Schmidt, Sebastian Möller · 2022
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 crowdsourcing 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.