Automated Scoring of Picture-based Story Narration

This work investigates linguistically motivated features for automatically scoring a spoken picture-based narration task. Specifically, we build scoring models with features for story development, language use and task relevance of the response. Results show that combinations of these features outperform a baseline system that uses state of the art speechbased features, and that best results are obtained by combining the linguistic and speech features.