Classification of Human- and AI-Generated Texts for English, French, German, and Spanish

Kristina Schaaff, Tim Schlippe, Lorenz Mindner
12/8/2023
cs.CLcs.AI

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Abstract

In this paper we analyze features to classify human- and AI-generated text for English, French, German and Spanish and compare them across languages. We investigate two scenarios: (1) The detection of text generated by AI from scratch, and (2) the detection of text rephrased by AI. For training and testing the classifiers in this multilingual setting, we created a new text corpus covering 10 topics for each language. For the detection of AI-generated text, the combination of all proposed features performs best, indicating that our features are portable to other related languages: The F1-scores are close with 99% for Spanish, 98% for English, 97% for German and 95% for French. For the detection of AI-rephrased text, the systems with all features outperform systems with other features in many cases, but using only document features performs best for German (72%) and Spanish (86%) and only text vector features leads to best results for English (78%).

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Cite this paper

@article{schaaff2023classification,
  title  = {Classification of Human- and AI-Generated Texts for English, French, German, and Spanish},
  author = {Kristina Schaaff and Tim Schlippe and Lorenz Mindner},
  year   = {2023},
  eprint = {2312.04882},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2312.04882v1}
}

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