A 2+1-level stochastic understanding model

In this paper, an extension of the 2-level stochastic understanding system is presented. An additional stochastic level is introduced in the system as the attribute value normalization module. In order to improve the model trainability, the conceptual decoding and value normalization steps are decoupled, leading to a 2+1-level system. The proposed approach is evaluated on the French MEDIA task (tourist information and hotel booking). This new 10k-utterance corpus is segmentally annotated allowing for a direct training of the 2-level conceptual models. Further developments of the system (modality propagation and hierarchical recomposition) are also investigated. On the whole, the proposed improvements achieve a 24% relative reduction of the understanding error rate from 37.6% to 28.8%