A speech recognition method uses a two-pass search to match an unknown utterance to a vocabulary word. Words in the vocabulary are represented by concatenated allophone models and the vocabulary is represented as a network. On the first pass of the search, a one-state duration constrained model is used to search the vocabulary network. The one-state model has as its transition probability the maximum observed transitional probability (model distance) of the unknown utterance for the corresponding allophone model. Words having top scores are chosen from the first pass search, and rescored using a full Viterbi trellis with the complete allophone models and model distances. The rescores are sorted to provide a few top choices. Using a second set of speech parameters these few top choices are again rescored. Comparison of the scores using each set of speech parameters determines a recognition choice. Post processing is also possible to further enhance recognition accuracy. Test results indicate that the two-pass search provides approximately the same recognition accuracy as a full Viterbi search of the vocabulary network.