  The problem of out of vocabulary words (OOV) is typical for any speech
recognition system, hybrid systems are usually constructed to recognize a fixed
set of words and rarely can include all the words that will be encountered
during exploitation of the system. One of the popular approach to cover OOVs is
to use subword units rather then words. Such system can potentially recognize
any previously unseen word if the word can be constructed from present subword
units, but also non-existing words can be recognized. The other popular
approach is to modify HMM part of the system so that it can be easily and
effectively expanded with custom set of words we want to add to the system. In
this paper we explore different existing methods of this solution on both graph
construction and search method levels. We also present a novel vocabulary
expansion techniques which solve some common internal subroutine problems
regarding recognition graph processing.
