Speech recognition system which selects one of a plurality of vocabulary models
First Claim
1. A computerized word recognition system comprising:
- means for receiving user generated word signals representing words;
means for defining a plurality of vocabulary words, including means for defining a plurality of word model sets, each of which defines a word model for each of said vocabulary words;
recognition means for pattern matching a word signal against a plurality of said word models to produce a recognition score for each such word model indicating the likelihood that said word model corresponds to said word signal; and
word model set selection means including;
set scoring means for causing said recognition means to pattern match each of one or more word signals against word models for one or more of said vocabulary words from each of said plurality of word model sets;
set selecting means for selecting a word model set whose one or more word models have the best recognition score against said one or more word signals; and
set favoring means for increasing the likelihood that said recognition means will expend more computation performing pattern matching against said selected word model set than against any other of said plurality of word model sets.
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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 state associated with that program unit into which vocabulary words which will be made active when that program group has the focus can be put; detect the available computational resources and alter the instructions it executes in response; test if its ability to respond to voice input has been shut off without user confirmation, and, if so, turn that ability back on and prompt the user to confirm if that ability is to be turned off; store both a first and a second set of models for individual vocabulary words and enable a user to selectively cause the recognizer to disregard the second set of models for a selected word; and/or score a signal representing a given word against models for that word from different word model sets to select which model should be used for future recognition.
323 Citations
27 Claims
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1. A computerized word recognition system comprising:
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means for receiving user generated word signals representing words; means for defining a plurality of vocabulary words, including means for defining a plurality of word model sets, each of which defines a word model for each of said vocabulary words; recognition means for pattern matching a word signal against a plurality of said word models to produce a recognition score for each such word model indicating the likelihood that said word model corresponds to said word signal; and word model set selection means including; set scoring means for causing said recognition means to pattern match each of one or more word signals against word models for one or more of said vocabulary words from each of said plurality of word model sets; set selecting means for selecting a word model set whose one or more word models have the best recognition score against said one or more word signals; and set favoring means for increasing the likelihood that said recognition means will expend more computation performing pattern matching against said selected word model set than against any other of said plurality of word model sets. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computer program recorded in machine readable memory for performing word recognition comprising:
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instructions for receiving user generated word signals representing words; instructions for defining a plurality of vocabulary words, including instructions for defining a plurality of word model sets, each of which defines a word model for each of said vocabulary words; recognition instructions for pattern matching a word signal against a plurality of said word models to produce a recognition score for each such word model indicating the likelihood that said word model corresponds to said word signal; and word model set selection instructions including; set scoring instructions for causing said recognition instructions to pattern match each of one or more word signals against word models for one or more of said vocabulary words from each of said plurality of word model sets; set selecting instructions for selecting a word model set whose one or more word models have the best recognition score against said one or more word signals; and set favoring instructions for increasing the likelihood that said recognition instructions will expend more computation performing pattern matching against said selected word model set than against any other of said plurality of word model sets. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19)
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20. A computerized method for performing word recognition comprising the steps of:
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receiving user generated word signals representing words; defining a plurality of vocabulary words, including defining a plurality of word model sets, each of which defines a word model for each of said vocabulary words; pattern matching of a word signal against a plurality of said word models to produce a recognition score for each such word model indicating the likelihood that said word model corresponds to said word signal; and word model set selection including the steps of; causing said pattern matching to be performed on each of one or more word signals against word models for one or more of said vocabulary words from each of said plurality of word model sets; selecting a word model set whose one or more word models have the best recognition score against said one or more word signals; and increasing the likelihood that more computation will be expended performing pattern matching against said selected word model set than against any other of said plurality of word model sets. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27)
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Specification