1. A computerized method for real-time spotting of predetermined keywords in an audio stream, in an automatic speech recognition system, wherein said system comprises at least a speech recognition engine, the method comprising the steps of: a) developing a keyword model for the predetermined keywords; b) comparing, in real-time, the keyword model and the audio stream to recognize candidates of the predetermined keywords in the audio stream; c) computing, by the speech recognition engine, a probability that a portion of the audio stream matches one of the predetermined keywords from the keyword model, wherein the probability is determined utilizing a posterior based probability approach which comprises analysis of monophone models over an audio feature space; d) comparing the computed probability of a keyword match to a predetermined threshold and declaring a match if the computed probability meets the predetermined threshold; e) computing further data to aid in determination of mismatches, wherein said further data comprises empirical metrics, and determining if the candidates are mismatches; and f) reporting spotted keywords if a mismatch is not identified at step (e), wherein the reporting comprises generating a report, via a microprocessor and software program, that is presented as a start and end time of the spotted keywords in the audio stream with the computed probability that the keywords were found.
4. The method of claim 1 , wherein step (c) comprises executing a Viterbi algorithm.