Adobe-MIT submission to the DSTC 4 Spoken Language Understanding pilot task
This work addresses spoken language understanding for dialog systems, but it appears incremental as it applies existing methods to a new challenge task.
The paper tackled the spoken language understanding task in DSTC 4 by comparing different classifiers, achieving F1-scores of 0.52 and 0.67 for speech act recognition and 0.52 for semantic tagging on test sets.
The Dialog State Tracking Challenge 4 (DSTC 4) proposes several pilot tasks. In this paper, we focus on the spoken language understanding pilot task, which consists of tagging a given utterance with speech acts and semantic slots. We compare different classifiers: the best system obtains 0.52 and 0.67 F1-scores on the test set for speech act recognition for the tourist and the guide respectively, and 0.52 F1-score for semantic tagging for both the guide and the tourist.