A further contribution of the thesis is a novel approach for the rapid generation of speech recognition capability in resource-poor languages. Since most languages spoken in the developing world have limited speech resources, it is difficult to create speech recognizers for such languages. My approach leverages existing off-the-shelf technology to create robust, speaker-independent, small-vocabulary speech recognition capability with minimal training data requirements. I empirically show that this method is able to reach recognition accuracies of greater than 90% with very little effort and, even more importantly, little speech technology skill. 
