This paper describes the addition of between-word coarticulation modeling into sphinx, an accurate large-vocabulary speaker-independent continuous speech recognition system. Between-word coarticulation is a major source of phonetic variability in continuous speech. By detailed modeling of between-word triphones and utilizing the generalized triphone technique, we obtain an error rate reduction of 16% to 29% for different test sets and grammars on the DARPA Resource Management (RM) Task.