47 citations · 143 across the 42 of their papers we have counts for
4 papers · 1 filter
Information Type Classification with Contrastive Task-Specialized Sentence Encoders
Philipp Seeberger, Tobias Bocklet, Korbinian Riedhammer
User-generated information content has become an important information source in crisis situations. However, classification models suffer from noise and event-related biases which…
Classifying Dementia in the Presence of Depression: A Cross-Corpus Study
Franziska Braun, Sebastian P. Bayerl, Paula A. Pérez-Toro +6
Automated dementia screening enables early detection and intervention, reducing costs to healthcare systems and increasing quality of life for those affected. Depression has shared…
A Stutter Seldom Comes Alone -- Cross-Corpus Stuttering Detection as a Multi-label Problem
Sebastian P. Bayerl, Dominik Wagner, Ilja Baumann +4
Most stuttering detection and classification research has viewed stuttering as a multi-class classification problem or a binary detection task for each dysfluency type; however, th…
Combining Deep Neural Reranking and Unsupervised Extraction for Multi-Query Focused Summarization
Philipp Seeberger, Korbinian Riedhammer
The CrisisFACTS Track aims to tackle challenges such as multi-stream fact-finding in the domain of event tracking; participants' systems extract important facts from several disast…