Comparison of Parsing and Spotting Approaches for Spoken Dialogue Understanding
Tatsuya Kawahara, Masahiro Araki, Shuji Doshita · Institutional Repositories DataBase (IRDB) · 1994
We have studied the optimal strategies for both LR parsing and spotting. In this report, several parsing and spotting approaches for spoken dialogue understanding are compared and evaluated. Here, a novel phrase spotting approach based on progressive search is proposed for robust understanding. The experimental results show that (1) sentence-level parsing is most powerful but not robust, (2) phrase spotting approach is robust against ill-formed utterances, (3) simple word bigram and word spotting get good word accuracy but do not lead to sentence-level understanding. Furthermore, we explore a hybrid approach where the sentence-level parsing is tried and, if it fails, the phrase spotting is performed.