Porzel, Robert ; Gurevych, Iryna ; Müller, Christof (2003)
Ontology-based contextual coherence scoring.
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
In this paper we present a contextual extension to ONTOSCORE, a system for scoring sets of concepts on the basis of an ontology. We apply the contextually enhanced system to the task of scoring alternative speech recognition hypotheses (SRH) in terms of their semantic coherence. We conducted several annotation experiments and showed that human annotators can reliably differentiate between semantically coherent and incoherent speech recognition hypotheses (both with and without discourse context). We also showed, that annotators can reliably identify the overall best hypothesis from a given n-best list. While the original ONTOSCORE system correctly assigns the highest score to 84.06% of the corpus, the inclusion of the conceptual context increases the number of correct classifications to yield 86.76%, given a baseline of 63.91% in both cases.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2003 |
| Autor(en): | Porzel, Robert ; Gurevych, Iryna ; Müller, Christof |
| Art des Eintrags: | Bibliographie |
| Titel: | Ontology-based contextual coherence scoring |
| Sprache: | Deutsch |
| Publikationsjahr: | 2003 |
| Buchtitel: | Proceedings of the Fourth SIGdial Workshop on Discourse and Dialogue |
| Kurzbeschreibung (Abstract): | In this paper we present a contextual extension to ONTOSCORE, a system for scoring sets of concepts on the basis of an ontology. We apply the contextually enhanced system to the task of scoring alternative speech recognition hypotheses (SRH) in terms of their semantic coherence. We conducted several annotation experiments and showed that human annotators can reliably differentiate between semantically coherent and incoherent speech recognition hypotheses (both with and without discourse context). We also showed, that annotators can reliably identify the overall best hypothesis from a given n-best list. While the original ONTOSCORE system correctly assigns the highest score to 84.06% of the corpus, the inclusion of the conceptual context increases the number of correct classifications to yield 86.76%, given a baseline of 63.91% in both cases. |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Telekooperation |
| Hinterlegungsdatum: | 31 Dez 2016 12:59 |
| Letzte Änderung: | 24 Jan 2020 12:03 |
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