Hybrid ensemble predictor as quality metric for German text summarization: Fraunhofer IAIS at GermEval 2020 task 3

We propose an alternative quality metric to evaluate automatically generated texts based on an ensemble of different scores, combining simple rule-based metrics with more complex models of very different nature, including ROUGE, tf-idf, neural sentence embeddings, and a matrix factorization method. Our approach achieved one of the top scores on the second German Text Summarization Challenge.