23. Word recognition apparatus comprising: input means for receiving successive user generated signals from a user, each of which represents a word to be recognized; means for storing a signal model for each of a plurality of vocabulary words; recognition means for scoring a match between each such user generated signal and each of a plurality of said signal models, and for selecting the word associated with the signal model which scores best against each user generated signal as the recognized word for that user generated signal; adaptive training means for altering the signal models of individual recognized words to take into account information derived from each such individual recognized word's associated user generated signal separately in response to the selection of each of said recognition words; and batch training means for altering the signal model of each of a plurality of words to take into account information derived from multiple user generated signals for which that word was selected as the recognized word in a multi-word sample of user generated signals, said batch training means introducing such information from multiple user genrated signals into that signal model in one training process.
27. Word recognition apparatus as in claim 23, wherein: said recognition means includes means for performing said scoring originally against non-user trained signal models, to that is, signal models which have not been trained by said given user; said adaptive training means includes means for starting said adaptive training for a given user by altering said non-user trained models to take into account said information derived from user generated signals from the given user, so as to cause those models to be at least partially trained by that user.