Abstract: New techniques and systems may be implemented to improve error correction in speech recognition. These new techniques and systems may be implemented to correct errors in speech recognition systems may be used in a standard desktop environment, in a mobile environment, or in any other type of environment that can receive and/or present recognized speech.

Abstract: Correcting incorrect text associated with recognition errors in computer-implemented speech recognition includes receiving a selection of a word from a recognized utterance. The selection indicates a bound of a portion of the recognized utterance to be corrected. A first recognition correction is produced based on a comparison between a first alternative transcript and the recognized utterance. A second recognition correction is produced based on a comparison between a second alternative transcript and the recognized utterance. The duration of the first recognition correction differs from the duration of the second recognition correction. A portion of the recognition result that is replaced with one of the first recognition correction and the second recognition correction. includes at one bound a word indicated by the selection and extends for the duration of the one of the first recognition correction and the second recognition correction with which the portion is replaced.

Abstract: A computer is used to perform recorded actions. The computer receives recorded spoken utterances of actions. The computer then performs speech recognition on the recorded spoken utterances to generate texts of the actions. The computer then parses the texts to determine properties of the actions. After parsing the texts, permits the user to indicate that the user has reviewed one or more actions. The computer then automatically carries out the actions indicated as having been reviewed by the user.

Abstract: An action position is manipulated in computer-implemented speech recognition by receiving data representing a spoken command. The command includes a command identifier (e.g., insert before, insert after, resume with) and a designation of at least one previously-spoken word. Speech recognition is performed on the data to identify the command identifier and the designation. Finally, an action position is established relative to the previously-spoken word based on the command identifier. Text may be selected using a spoken selection command that includes a command identifier and a text block identifier identifying a block of previously-recognized text. At least one word included in the block of text is not included in the text block identifier.

Abstract: New techniques and systems may be implemented to improve error correction in speech recognition. These new techniques and systems may be implemented to correct errors in speech recognition systems may be used in a standard desktop environment, in a mobile environment, or in any other type of environment that can receive and/or present recognized speech.

Abstract: A computer enrolls a user in a speech recognition system by obtaining data representing a user's speech, the speech including multiple user utterances and generally corresponding to an enrollment text, and analyzing acoustic content of data corresponding to a user utterance. The computer determines, based on the analysis, whether the user utterance matches a portion of the enrollment text. If so, the computer uses the acoustic content of the user utterance to update acoustic models corresponding to the portion of the enrollment text. The computer may determine that the user utterance matches a portion of the enrollment text even when the user has skipped or repeated words of the enrollment text.

Abstract: Language model results are combined according to a combination expression to produce combined language model results for a set of candidates. A candidate is selected and the combination expression is adjusted using language model results associated with the selected candidate.

Abstract: A computer enrolls a user in a speech recognition system by obtaining data representing a user's speech, the speech including multiple user utterances and generally corresponding to an enrollment text, and analyzing acoustic content of data corresponding to a user utterance. The computer determines, based on the analysis, whether the user utterance matches a portion of the enrollment text. If so, the computer uses the acoustic content of the user utterance to update acoustic models corresponding to the portion of the enrollment text. The computer may determine that the user utterance matches a portion of the enrollment text even when the user has skipped or repeated words of the enrollment text.

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: In a method for use in recognizing continuous speech, signals are accepted corresponding to interspersed speech elements including text elements corresponding to text to be recognized and command elements corresponding to commands to be executed. The elements are recognized. The recognized elements are acted on in a manner which depends on whether they represent text or commands.

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 speech recognition system includes a speech-response capability for responding to sounds which appear to match models of spoken words by performing functions associated with such words. This speech response can be turned on or off. If the system detects both that speech response is off and that no indication is stored that the off state has been confirmed by a user, it performs a confirmation process. This prompts the user to utter a phrase confirming whether or not speech response is to be off; turns speech response on so it can respond to the user's confirmation utterance; determines whether to leave speech response on or off in response to the word which the speech response selects as corresponding to the user's confirmation utterance; and responds to such a determination that speech response is to be turned off, both by turning it off and by storing an indication that the off state has been confirmed by the user.

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 computerized system performs word recognition. It does pattern matching to select which vocabulary words appears, according to the pattern matching, to most probably correspond to word signals it seeks to recognize. It produces an output corresponding to the vocabulary words selected at a movable cursor position in a body of text. The system improves its recognition by obtaining information about the linguistic context of the current cursor position in the body of text and using that information to vary the probability of which one or more words is selected by its pattern matching. The pattern matching can be speech recognition performed on signals representing the sound of spoken words.

Abstract: A computerized word recognition system, such as a speech recognition system, stores word models of a first and second set for each of a plurality of vocabulary words. The system has a user interface which enable a user to selectively prevent the use of a second set's word model for a selected word. Often the first set of word models are spelled word models, such as models represented by a sequence of phonetic component models, each of is derived from similar speech sounds occurring in different words. In such systems the second set of word models are custom words models derived largely from word signals which are presumed to correspond only to the model's associated word. In many embodiments, the user interface allows a user to select to stop using a selected word's custom, or second set, model by selecting a menu or control window of a user interface.

Abstract: A word recognition system detects the computational resources available to it, such as the speed or number of processors, or whether there is DSP hardware, and alters the instructions it executes in response. The system can be a word recognition program designed to run on different computers having different computational resources. The program receives user generated word signals representing words to be recognized; performs pattern matching on them to select which vocabulary words most probably correspond to such word signals; detects if certain computational resources are available; and varies the instructions it executes in response. In many embodiments the system is a speech recognition program. The word recognition program can vary the computational intensity of its signal processing as a function of available computational resources. Preferably it can match the same word models against representations of word signals produced both by its more and less intensive signal processing.

Abstract: A computerized speech recognition system creates acoustic models of phrases by concatenating acoustic models for individual words. The system stores an acoustic word model and spelling for each of its vocabulary words. When it receives the spelling of a multi-word phrase to be treated as a new vocabulary word, it stores that multi-word spelling as the spelling of the new vocabulary word, and a new acoustic model created by concatenating the acoustic word models of previous vocabulary words whose spellings correspond to words in the multi-word spelling as the acoustic model for the new word. The system can then perform speech recognition by comparing acoustic signals against the word models of stored vocabulary words, including those representing such multi-word phrases. Preferably when a multi-word model is formed, the individual acoustic models concatenated are modified to represent the coarticulation which takes place between words spoken continuously.

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: An element (e.g., a location pointer in a windowed graphical user interface) shown on a computer display is moved toward a target position. A user's input is recognized which identifies a subregion of the display in which the target position is located. The element is moved discontinuously to a location within the identified subregion. Then a next user's input is recognized which identifies a sub-subregion of the subregion of the display in which the target position is located. The element is moved discontinuously to a location within the identified sub-subregion. In another aspect, an element is dragged between two locations on a computer display. User commands are accepted which indicate the two locations. Then the element is dragged between them. The user commands identify a sequence of discontinuous jumps for moving the element to the indicated location.

Abstract: In a method for use in recognizing continuous speech, signals are accepted corresponding to interspersed speech elements including text elements corresponding to text to be recognized and command elements corresponding to commands to be executed. The elements are recognized. The recognized elements are acted on in a manner which depends on whether they represent text or commands.