no code implementations • COLING (LaTeCHCLfL, CLFL, LaTeCH) 2020 • Bernhard Liebl, Manuel Burghardt
In this paper we describe an approach for the computer-aided identification of Shakespearean intertextuality in a corpus of contemporary fiction.
no code implementations • COLING (LaTeCHCLfL, CLFL, LaTeCH) 2020 • Miriam Amin, Manuel Burghardt
We provide a comprehensive overview of existing systems for the computational generation of verbal humor in the form of jokes and short humorous texts.
no code implementations • 6 Aug 2020 • Bernhard Liebl, Manuel Burghardt
We investigate how to train a high quality optical character recognition (OCR) model for difficult historical typefaces on degraded paper.
1 code implementation • 15 Apr 2020 • Bernhard Liebl, Manuel Burghardt
One important and particularly challenging step in the optical character recognition (OCR) of historical documents with complex layouts, such as newspapers, is the separation of text from non-text content (e. g. page borders or illustrations).
no code implementations • COLING 2018 • Thomas Schmidt, Manuel Burghardt
We discuss the problems and challenges for sentiment analysis in this area and describe our next steps toward further research.
no code implementations • LREC 2016 • Manuel Burghardt, Daniel Granvogl, Christian Wolff
Data acquisition in dialectology is typically a tedious task, as dialect samples of spoken language have to be collected via questionnaires or interviews.