1. A method for identifying a possible error made by a speech recognition system comprising: with an apparatus using at least one hardware-implemented processor, identifying when a hypothesis generated by the speech recognition system does not match an expected response word-for-word, but the hypothesis mostly matches the expected response word-for-word; with the apparatus using the at least one hardware-implemented processor, identifying an instance where the speech recognition system rejects a first hypothesis of a first utterance received from a user, followed by the speech recognition system accepting a second hypothesis of a second utterance received from the user, wherein the first and second hypotheses substantially match word-for-word; with the apparatus using the at least one hardware-implemented processor, incrementing a count of an occurrence of a possible error made by the speech recognition system; and with the apparatus using the at least one hardware-implemented processor, adjusting an adaptation of a model used by the speech recognition system for a word associated with the possible error when the count exceeds an acceptance threshold.
1. A method for identifying a possible error made by a speech recognition system comprising: with an apparatus using at least one hardware-implemented processor, identifying when a hypothesis generated by the speech recognition system does not match an expected response word-for-word, but the hypothesis mostly matches the expected response word-for-word; with the apparatus using the at least one hardware-implemented processor, identifying an instance where the speech recognition system rejects a first hypothesis of a first utterance received from a user, followed by the speech recognition system accepting a second hypothesis of a second utterance received from the user, wherein the first and second hypotheses substantially match word-for-word; with the apparatus using the at least one hardware-implemented processor, incrementing a count of an occurrence of a possible error made by the speech recognition system; and with the apparatus using the at least one hardware-implemented processor, adjusting an adaptation of a model used by the speech recognition system for a word associated with the possible error when the count exceeds an acceptance threshold. 2. The method of claim 1 , wherein the first hypothesis and the second hypothesis substantially match word-for-word by matching word-for-word, except that one of the first hypothesis and the second hypothesis includes at least one additional recognized model that is negligible for purposes of identifying the possible error.