21. The method of claim 19, wherein the baseform corresponding to the silence is represented by two consecutive silence phones.
19. In a speech recognition system which recognizes a spoken utterance consisting of an input sequence of spoken words and outputs a sequence of decoded words, a method for automatically punctuating the decoded words comprises the steps of: training an acoustic model; training an n-gram language model; building a vocabulary of items, the items including words and punctuation marks, said building step including assigning at least one baseform to each of the punctuation marks in the vocabulary, the at least one baseform corresponding to at least one of silence and a non-word noise, the vocabulary defining the items for which language model scores exist; defining conditional probabilities for the punctuation marks in the language model based upon at least one of at least one preceding word and at least one succeeding word; and generating a word match score corresponding to the probability that a subject punctuation mark in the vocabulary corresponds to acoustic data generated by said utterance; generating a language model score corresponding to the probability that the subject punctuation mark corresponds to acoustic data generated by said utterance; and automatically inserting the subject punctuation mark at a given point in the sequence of decoded words when the combination of the word match score and the language model score produces the highest combined likelihood over any other item in the vocabulary for the given point.