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 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 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: Words are added to a speech recognition system vocabulary during user dictation by (a) extracting, from a multi-word user utterance, speech frames that correspond to each one of the one or more new words; and (b) building speech models for the one or more new words using the extracted speech frames.

Abstract: A system and associated methods for recognizing compound words from an utterance containing a succession of one or more words from a predetermined vocabulary. At least one of the words in the utterance is a compound word including at least two formatives in succession, wherein those formatives are words in the vocabulary.

Abstract: A speech detection system compares the amplitude of an audio signal during successive time periods with speech detection thresholds, and generates an indication of whether the signal contains speech. It derives a background amplitude level from portions of the signal which it indicates do not contain speech, and improves its speech detection by altering the amplitude of the audio signal relative to the speech detection thresholds as a function of this background level. Preferably the background amplitude level is a moving average, which is repeatedly recalculated and repeatedly used to alter the relative amplitude of the audio signal and the detection thresholds. The apparatus uses a measure of the variability of the background amplitude to improve its speech detection. It generates start-of-speech and end-of-speech indications when the amplitude crosses respective thresholds for specified numbers of frames.