The project deals with the Quality of Experience of machine-generated texts. The focus lies on the two text types Machine Translation and Automatic Text Summarization. The goals of the project are to identify perceptive quality dimensions, to provide subjective methods for the quantification of the quality dimensions, to determine automatically extractable factors that correlate with text quality, and to develop prediction models that can assess the overall quality of a machine-generated text.
Please cite the following publication:
Dinh Nam Pham, Vivien Macketanz, Shushen Manakhimova, Sebastian Möller. 2025. In: Proceedings of the 21st Conference on Natural Language Processing (KONVENS 2025): Workshops. (2025)
@inproceedings{pham-etal-2025-modeling,
title = "Modeling Quality of Experience in {G}erman Automatic Text Summarization and Machine Translation",
author = {Pham, Dinh Nam and
Macketanz, Vivien and
Manakhimova, Shushen and
M{\"o}ller, Sebastian},
editor = "Wartena, Christian and
Heid, Ulrich",
booktitle = "Proceedings of the 21st Conference on Natural Language Processing (KONVENS 2025): Workshops",
month = sep,
year = "2025",
address = "Hannover, Germany",
publisher = "HsH Applied Academics",
url = "https://aclanthology.org/2025.konvens-2.12/",
pages = "169--175"
}