German Text

Research on German text processing focuses on improving the accuracy and efficiency of natural language processing (NLP) tasks. Current efforts concentrate on text simplification, particularly for accessibility and legal contexts, employing transformer-based neural language models but facing challenges due to data scarcity and the complexities of German grammar. These advancements are crucial for enhancing accessibility for individuals with cognitive or linguistic impairments and improving the efficiency of various NLP applications, such as information extraction and temporal expression recognition. Furthermore, work is underway to improve named entity recognition for domain-specific German texts, enabling more accurate analysis of specialized corpora.