; Department of Computer Science and Engineering, Pohang University of Science & Technology (POSTECH), San 31, Hyoja-Dong, Pohang, 790-784, Korea. firstname.lastname@example.org
Gary Geunbae Lee
Spoken language understanding (SLU) aims to map a user's speech into a semantic frame. Since most of the previous works use the semantic structures for SLU, we verify that the structure is valuable even for noisy input. We apply a structured prediction method to SLU problem with comparison to unstructured one. In addition, we present a combined method to embed long-distance dependency between entities in a cascaded manner. On air travel data, we show that our approach improves performance over baseline models.