A network-based frame-synchronous level building algorithm for connected word recognition

A network-based, frame-synchronous, level building (FSLB) algorithm is described for recognizing continuous speech as a connected sequence of words. Previous frame synchronous approaches to recognition have included the one-pass approach, the one-stage approach, and an unpublished multilevel approach. The proposed algorithm, which has all the features of these earlier methods, as well as several new features, and which is implemented in a network-based approach, is a numerically exact, frame synchronous, implementation of the conventional level building (LB) algorithm. As with some of the earlier methods, the proposed algorithm is highly regular and modularized for distributed computation among several spectral purpose processors. New features of the algorithm include the capability of determining the best alternative recognition strings (e.g. second and third best strings), at every level, even for very complicated grammar networks, and the capability of efficiently incorporating several word and state duration scoring techniques directly in the forward search thereby eliminating the need for a postprocessor as required in the direct LB implementation. Word transition rules (e.g. a language model) can also be easily incorporated into the proposed algorithm