Patent Document ID: 8959019
Application ID: 11932122

Base Claim:
1. A method for determining an empirically derived acoustic confusability measure, comprising the steps of: using a computer for performing corpus processing by initially processing an original corpus, comprising both audio information and a true transcription thereof, with an automatic speech recognition system of interest once, one utterance at a time to produce a recognized corpus comprising a machine transcription of audio information; and developing a family of phoneme confusability models by repeatedly processing said recognized corpus with said computer, after the corpus is initially processed by said automatic speech recognition system once, wherein each repetition comprises the steps of: setting all phoneme pair counts to zero; and analyzing to analyze each pair of phoneme sequences in said recognized corpus to collect information regarding the confusability of any two phonemes, wherein said information is collected by: constructing a lattice from each said pair of phoneme sequences; labeling each arc of the lattice with the appropriate value from the current family of decoding costs; computing the minimum cost path through this lattice; and traversing said minimum cost path and incrementing the phoneme pair count for each arc that is traversed; and upon completion for each said pair of phoneme sequences of said minimum cost path traversal and associated incrementing of phoneme pair counts, using said accumulated phoneme pair counts to deliver a family of phoneme confusability models.

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Claim 4:
4. The method of claim 1 , said developing step comprising the steps of: iterating until there is no further change in said family of confusability models, or the change becomes negligible; outputting said family of confusability models, which estimates acoustic confusability of any two members a augmented phoneme alphabet; and deriving an acoustic confusability measure.