Incorporating Discourse Features into Confidence Scoring of Intention Recognition Results in Spoken Dialogue Systems
Ryuichiro Higashinaka, Katsuhito Sudoh, Mikio Nakano · 2006
The paper proposes a method for the confidence scoring of intention recognition results in spoken dialogue systems. To achieve tasks, a spoken dialogue system has to recognize user intentions. However, because of speech recognition errors and ambiguity in user utterances, it sometimes has difficulty recognizing them correctly. Confidence scoring allows errors to be detected in intention recognition results and has proved useful for dialogue management. Conventional methods use the features obtained from speech recognition results for single utterances for confidence scoring. However, this may be insufficient since the intention recognition result is a result of discourse processing. We propose incorporating discourse features for a more accurate confidence scoring of intention recognition results. Experimental results show that incorporating discourse features significantly improves the confidence scoring.