Abstract

The Dublin City University participation in the CLEF 2005 CL-SR task concentrated on exploring the application of our existing information retrieval methods based on the Okapi model to the conversational speech data set. This required an approach to determining approximate sentence boundaries within the free-flowing automatic transcription provided to enable us to use out summary-based pseudo relevance feedback (PRF). We also performed exploratory experiments on the use of the metadata provided with the document transcriptions. Topics were translated into English using Systran V3.0 machine translation. In most cases Title field only topic statements performed better than combined Title and Description topics. PRF using our adapted methods is shown to be affective, and absolute performance is improved by combining the automatic document transcriptions with additional metadata fields.