3. The method of claim 1 , the steps of constructing said lattice, populating said lattice arcs with values drawn from a current family of decoding costs, applying said Bellman-Ford dynamic programming algorithm, or said Dijkstra's shortest path algorithm, to find said shortest path through said lattice, and traversing said determined shortest path, wherein for each arc that is traversed, the phoneme pair count is incremented by 1, comprising: for an entry in the recognized corpus with a decoded phoneme sequence containing N phonemes, and a true phoneme sequence containing Q phonemes, constructing a rectangular lattice of dimension (N+1) rows by (Q+1) columns, and with an arc from a node (i, j) to each of nodes (i+1, j), (i, j+1), and (i+1, j+1), when present in said lattice, where “node (i, j)” refers to the node in row i, column j of the lattice; labeling: each arc from node (i, j) to node (i, j+1) with the cost δ (m) (ε|t j ) each arc from node (i, j) to node (i+1, j) with the cost δ (m) (d i |ε) each arc from node (i, j) to node (i+1, j+1) with the cost δ (m) (d i |t j ), where δ (m) is the associated decoding cost at the mth iteration of the algorithm, and applying the Bellman-Ford dynamic programming algorithm or Dijkstra's shortest path algorithm to find a shortest path from the source node, which is defined as node (0, 0), to the terminal node, which is defined as node (N, Q); outputting a sequence of arcs A=a 1 , a 2 , . . . , a K , in said lattice corresponding to the aforesaid minimum cost path from the source node to the terminal node; and for each arc a i in the minimum cost path A, labeled with a phoneme pair, incrementing the associated phoneme pair count by 1.
1. In a computer implemented method for determining an empirically derived acoustic confusability measure, an iterative method for development of a probability model family Π={p(d|t)}, comprising: providing a recognized corpus; establishing a termination condition which depends on any of: a number of iterations executed; and closeness of match between a previous and current probability family models; defining a family of decoding costs; setting an iteration count to 0; setting a phoneme pair count to 0; for each entry in the recognized corpus, performing the following steps: constructing a lattice; populating lattice arcs with values drawn from a current family of decoding costs; applying a Bellman-Ford dynamic programming algorithm, or a Dijkstra's shortest path algorithm, to find a shortest path through said lattice, from a source node to a terminal node; and traversing said determined shortest path, wherein for each arc that is traversed, the phoneme pair count is incremented by 1; for each transcription, computing a confidence score which is the sum of a phoneme pair value over all transcriptions paired with an utterance; estimating said probability model family; if the iteration count exceeds 0, testing said termination condition; if said termination condition is satisfied, returning a desired probability model family and stopping; if said termination condition is not satisfied, defining a new family of decoding costs and therefrom a new probability model family; and incrementing said iteration count and repeating.