Handling Out-of-Grammar Commands in Mobile Speech Interaction Using Backoff Filler Models

In command and control (C&C) speech interaction, users interact by speaking commands or asking questions typically specified in a context-free grammar (CFG). Unfortunately, users often produce out-ofgrammar (OOG) commands, which can result in misunderstanding or nonunderstanding. We explore a simple approach to handling OOG commands that involves generating a backoff grammar from any CFG using filler models, and utilizing that grammar for recognition whenever the CFG fails. Working within the memory footprint requirements of a mobile C&C product, applying the approach yielded a 35% relative reduction in semantic error rate for OOG commands. It also improved partial recognitions for enabling clarification dialogue.