11. In a speech recognition system which recognizes a spoken utterance and, in response, outputs a sequence of decoded words, a method for automatically punctuating the sequence of decoded words comprises the steps of: assigning at least one baseform to a subject punctuation mark in a vocabulary of words and punctuation marks, the at least one baseform including at least one of a silence phone, two consecutive silence phones, at least one consonant phone preceded and followed by the silence phone, at least one vowel phone preceded and followed by the silence phone, and at least one consonant phone and at least one vowel phone preceded and followed by the silence phone, the vocabulary defining items for which language model scores exist; defining at least one conditional probability for the subject punctuation mark in a 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 the subject punctuation mark corresponds to acoustic data generated by said utterance; generating a language model score corresponding to the probability that the subject punctuation mark corresponds to the acoustic data generated by said utterance; and automatically inserting the subject punctuation mark at a given position 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 word and punctuation mark in the vocabulary for the given position.
11. In a speech recognition system which recognizes a spoken utterance and, in response, outputs a sequence of decoded words, a method for automatically punctuating the sequence of decoded words comprises the steps of: assigning at least one baseform to a subject punctuation mark in a vocabulary of words and punctuation marks, the at least one baseform including at least one of a silence phone, two consecutive silence phones, at least one consonant phone preceded and followed by the silence phone, at least one vowel phone preceded and followed by the silence phone, and at least one consonant phone and at least one vowel phone preceded and followed by the silence phone, the vocabulary defining items for which language model scores exist; defining at least one conditional probability for the subject punctuation mark in a 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 the subject punctuation mark corresponds to acoustic data generated by said utterance; generating a language model score corresponding to the probability that the subject punctuation mark corresponds to the acoustic data generated by said utterance; and automatically inserting the subject punctuation mark at a given position 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 word and punctuation mark in the vocabulary for the given position. 12. The method of claim 11, wherein each word, silence and punctuation mark in the vocabulary is represented by at least one baseform.