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.

Publisher  Association for Computational Linguistics
All copyrights reserved by ACL 2007

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