  This study is devoted to the automatic generation of German drama texts. We
suggest an approach consisting of two key steps: fine-tuning a GPT-2 model (the
outline model) to generate outlines of scenes based on keywords and fine-tuning
a second model (the generation model) to generate scenes from the scene
outline. The input for the neural model comprises two datasets: the German
Drama Corpus (GerDraCor) and German Text Archive (Deutsches Textarchiv or DTA).
In order to estimate the effectiveness of the proposed method, our models are
compared with baseline GPT-2 models. Our models perform well according to
automatic quantitative evaluation, but, conversely, manual qualitative analysis
reveals a poor quality of generated texts. This may be due to the quality of
the dataset or training inputs.
