An efficient search method for large-vocabulary continuous-speech recognition

This paper proposes an efficient method for large-vocabulary continuous-speech recognition, using a compact data structure and an efficient search algorithm. We introduce a very compact data structure DAWG as a lexicon to reduce the search space. We also propose a search algorithm to obtain the N-best hypotheses using the DAWG structure. This search algorithm is composed of two phases: “forward search” and “traceback”. Forward search, which basically uses the time-synchronous Viterbi algorithm, merges candidates and stores the information about them in DAWG structures to create phoneme graphs. Traceback traces the phoneme graphs to obtain the N-best hypotheses. An evaluation of this method´s performance using a speech-recognition-based telephone-directory-assistance system having a 4000-word vocabulary confirmed that our strategy improves speech recognition in terms of time and recognition rate