We describe DCU's participation in the NTCIR-11 Spoken-Query&Document task. We participated in the spoken query spoken content retrieval (SQ-SCR) subtask by using the slide group segments as basic indexing and retrieval units. Our approach integrates normalised prosodic features into a standard BM25 weighting function to increase weights for terms that are prominent in speech. Text queries and relevance assessment data from the NTCIR-10 SpokenDoc-2 passage retrieval task were used to train the prosodic-based models. Evaluation results indicate that our prosodic-based retrieval models do not provide significant improvements over a text-based BM25 model, but suggest that they can be useful for certain queries.