7. An automatic speech recognition system, comprising: a speech processing subsystem that inputs an electrical signal representing an uttered speech and outputs a feature vector lattice; and a speech recognizer that inputs the feature vector lattice and outputs a text string representing the uttered speech; wherein the speech recognizer converts the feature vector lattice to the text string using at least one approximate weighted finite-state lattice; means for determinizing, for each approximate weighted finite-state lattice, a corresponding non-deterministic weighted finite-state lattice on a state-by-state basis to form that approximate weighted finite-state lattice; means for determining, as each set of states of the corresponding non-deterministic weighted finite-state lattice reachable from a current state of that approximate weighted finite-state lattice is determinized to form at least one proposed new state of that approximate weighted finite-state lattice, for each proposed new state, if that proposed new state is sufficiently similar to a previous state of that approximate weighted finite-state lattice; means for creating a transition from the current state of that approximate weighted finite-state lattice to the previous state of that approximate weighted finite-state lattice if that proposed new state is sufficiently similar to the previous state; and means for creating a transition from the current state of that approximate weighted finite-state lattice to the proposed new state of that approximate weighted finite-state lattice if that proposed new state is not sufficiently similar to any previous state of that approximate weighted finite-state lattice.
7. An automatic speech recognition system, comprising: a speech processing subsystem that inputs an electrical signal representing an uttered speech and outputs a feature vector lattice; and a speech recognizer that inputs the feature vector lattice and outputs a text string representing the uttered speech; wherein the speech recognizer converts the feature vector lattice to the text string using at least one approximate weighted finite-state lattice; means for determinizing, for each approximate weighted finite-state lattice, a corresponding non-deterministic weighted finite-state lattice on a state-by-state basis to form that approximate weighted finite-state lattice; means for determining, as each set of states of the corresponding non-deterministic weighted finite-state lattice reachable from a current state of that approximate weighted finite-state lattice is determinized to form at least one proposed new state of that approximate weighted finite-state lattice, for each proposed new state, if that proposed new state is sufficiently similar to a previous state of that approximate weighted finite-state lattice; means for creating a transition from the current state of that approximate weighted finite-state lattice to the previous state of that approximate weighted finite-state lattice if that proposed new state is sufficiently similar to the previous state; and means for creating a transition from the current state of that approximate weighted finite-state lattice to the proposed new state of that approximate weighted finite-state lattice if that proposed new state is not sufficiently similar to any previous state of that approximate weighted finite-state lattice. 12. The automatic speech recognition system of claim 7, wherein each at least one approximate weighted finite-state lattice corresponds to a non-deterministic weighted finite-state lattice and is an approximation of a deterministic weighted finite-state lattice generated from the corresponding non-deterministic weighted finite-state lattice.