This chapter introduces a simulator for incremental human-machine dialogue in order to generate artificial dialogue datasets that can be used to train and test data-driven methods. We review the various simulator components in detail, including an unstable speech recognizer, and their differences with non-incremental approaches. Then, as an illustration of its capacities, an incremental strategy based on hand-crafted rules is implemented and compared to several non-incremental baselines. Their performances in terms of dialogue efficiency are presented under different noise conditions and prove that the simulator is able to handle several configurations which are representative of real usages.
CITATION STYLE
Khouzaimi, H., Laroche, R., & Lefèvre, F. (2017). Incremental human-machine dialogue simulation. In Lecture Notes in Electrical Engineering (Vol. 427 427 LNEE, pp. 53–66). Springer Verlag. https://doi.org/10.1007/978-981-10-2585-3_4
Mendeley helps you to discover research relevant for your work.