Abstract: A word recognition system can: respond to the input of a character string from a user by limiting the words it will recognize to words having a related, but not necessarily the same, string; score signals generated after a user has been prompted to generate a given word against words other than the prompted word to determine if the signal should be used to train the prompted word; vary the number of signals a user is prompted to generate to train a given word as a function of how well the training signals score against each other or prior models for the prompted word; create a new acoustic model of a phrase by concatenating prior acoustic models of the words in the phrase; obtain information from another program running on the same computer, such as its commands or the context of text being entered into it, and use that information to vary which words it can recognize; determine which program unit, such as an application program or dialog box, currently has input focus on its computer and create a vocabulary

Abstract: A word recognition system is disclosed for converting spoken utterances into either text or commands. The system runs on a platform capable of running a plurality applications. Text and commands are sent from a word recognition application to one or more user applications. In addition, information pertaining to the state of the user applications is sent back to the word recognition application. Word recognition probabilities are modified based the information received from the user applications. As a result, the probabilities of recognizing a spoken utterance as a particular command will be greater when that command is active in the user application then when it is not active. Also, text strings will be assigned higher probabilities when they are appropriate for the present state of the user application.

Abstract: A word recognition system can: respond to the input of a character string from a user by limiting the words it will recognize to words having a related, but not necessarily the same, string; score signals generated after a user has been prompted to generate a given word against words other than the prompted word to determine if the signal should be used to train the prompted word; vary the number of signals a user is prompted to generate to train a given word as a function of how well the training signals score against each other or prior models for the prompted word; create a new acoustic model of a phrase by concatenating prior acoustic models of the words in the phrase; obtain information from another program running on the same computer, such as its commands or the context of text being entered into it, and use that information to vary which words it can recognize; determine which program unit, such as an application program or dialog box, currently has input focus on its computer and create a vocabulary

Abstract: A tutorial instructs how to use a word recognition system, such as one for speech recognition. It specifies a set of allowed response words for each of a plurality of states. It sends messages on how to use the recognizer in certain states, and, in others, presents exercises in which the user is to enter signals representing expected words. It scores each such signal against word models to select which response word corresponds to it, and then advances to a state associated with that selected response. This scoring is performed against a large vocabulary even though only a small number of responses are allowed, and the signal is rejected if too many non-allowed words score better than any allowed word. The system comes with multiple sets of standard signal models; it scores each against a given user's signals, selects the set which scores best, and then performs adaptive and batch training upon that set.