Which system differences matter?: using l1/l2 regularization to compare dialogue systems

We investigate how to jointly explain the performance and behavioral differences of two spoken dialogue systems. The Join Evaluation and Differences Identification (JEDI), finds differences between systems relevant to performance by formulating the problem as a multi-task feature selection question. JEDI provides evidence on the usefulness of a recent method, l1/lp-regularized regression (Obozinski et al., 2007). We evaluate against manually annotated success criteria from real users interacting with five different spoken user interfaces that give bus schedule information.