Semantic Coherence Scoring Using an Ontology 
 In this paper we present ONTOSCORE , a system for scoring sets of concepts on the basis of an ontology . We apply our system to the task of scoring alternative speech recognition hypotheses (SRH) in terms of their semantic coherence . We conducted an annotation experiment and showed that human annotators can reliably differentiate between semantically coherent and incoherent speech recognition hypotheses . An evaluation of our system against the annotated data shows that, it successfully classifies 73.2% in a German corpus of 2.284 SRHs as either coherent or incoherent (given a baseline of 54.55%). 