1. A method of automatic speech recognition, comprising the steps of: (a) receiving an utterance from a user via a microphone that converts the utterance into a speech signal; (b) pre-processing the speech signal using a processor to extract acoustic data from the received speech signal; (c) identifying at least one user-specific characteristic in response to the extracted acoustic data, wherein the at least one user-specific characteristic comprises a plurality of confidence scores associated with failed attempts of the user to store a nametag; and (d) determining a user-specific confidence threshold responsive to the at least one user-specific characteristic, wherein the determination is carried out by calculating an average of the plurality of confidence scores and setting the user-specific confidence threshold to a value greater than or equal to the calculated average.
1. A method of automatic speech recognition, comprising the steps of: (a) receiving an utterance from a user via a microphone that converts the utterance into a speech signal; (b) pre-processing the speech signal using a processor to extract acoustic data from the received speech signal; (c) identifying at least one user-specific characteristic in response to the extracted acoustic data, wherein the at least one user-specific characteristic comprises a plurality of confidence scores associated with failed attempts of the user to store a nametag; and (d) determining a user-specific confidence threshold responsive to the at least one user-specific characteristic, wherein the determination is carried out by calculating an average of the plurality of confidence scores and setting the user-specific confidence threshold to a value greater than or equal to the calculated average. 3. The method of claim 1 , further comprising the step of: (e) using the user-specific confidence threshold to assess confusability of the utterance with stored vocabulary, wherein the user-specific confidence threshold is a confusability confidence threshold.