Search and rescoring method for a speech recognition system

摘要

Speech recognition systems and methods consistent with the present invention process input speech signals organized into a series of frames. The input speech signal is decimated to select K frames out of every L frames of the input speech signal according to a decimation rate K/L. A first set of model distances is then calculated for each of the K selected frames of the input speech signal, and a Hidden Markov Model (HMM) topology of a first set of models is reduced according to the decimation rate K/L. The system then selects a reduced set of model distances from the computed first set of model distances according to the reduced HMM topology and selects a first plurality of candidate choices for recognition according to the reduced set of model distances. A second set of model distances is computed, using a second set of models, for a second plurality of candidate choices, wherein the second plurality of candidate choices correspond to at least a subset of the first plurality of candidate choices. The second plurality of candidate choices are rescored using the second set of model distances, and a recognition result is selected from the second plurality of candidate choices according to the rescored second plurality of candidate choices.