Abstract: A system and method are provided herein to support text and data entry for computer applications and the collection, processing, storage, and display of associated text, audio, image, video, and related data.

Abstract: This is a voice activated Hypermedia system using grammatical metadata, the system comprising: a speech user agent; a browsing module; and an information resource. The system may include: embedded intelligence in hypermedia source; a means for processing the actions of a user based on the embedded intelligence; a means for returning a result of the actions to the user. In addition, the hypermedia source maybe a HTML page or an instructional module for communicating allowed actions by a user. The system may also include embedded intelligence as a grammar or reference to a grammar. The grammar may be dynamically added to a speech recognizer. In addition, the actions can come from a speech recognizer. Furthermore, the system may include voice activated hypermedia links and intelligent modules that process information from the information resources for allowing actions from the user. Other devices, systems and methods are also disclosed.

Abstract: A system and method are provided herein to support text and data entry for computer applications and the collection, processing, storage, and display of associated text, audio, image, video, and related data.

Abstract: This is a voice activated Hypermedia system using grammatical metadata, the system comprising: a speech user agent; a browsing module; and an information resource. The system may include: embedded intelligence in hypermedia source; a means for processing the actions of a user based on the embedded intelligence; a means for returning a result of the actions to the user. In addition, the hypermedia source maybe a HTML page or an instructional module for communicating allowed actions by a user. The system may also include embedded intelligence as a grammar or reference to a grammar. The grammar may be dynamically added to a speech recognizer. In addition, the actions can come from a speech recognizer. Furthermore, the system may include voice activated hypermedia links and intelligent modules that process information from the information resources for allowing actions from the user. Other devices, systems and methods are also disclosed.

Abstract: This is a voice activated Hypermedia system using grammatical metadata, the system comprising: a speech user agent; a browsing module; and an information resource. The system may include: embedded intelligence in hypermedia source; a means for processing the actions of a user based on the embedded intelligence; a means for returning a result of the actions to the user. In addition, the hypermedia source maybe a HTML page or an instructional module for communicating allowed actions by a user. The system may also include embedded intelligence as a grammar or reference to a grammar. The grammar may be dynamically added to a speech recognizer. In addition, the actions can come from a speech recognizer. Furthermore, the system may include voice activated hypermedia links and intelligent modules that process information from the information resources for allowing actions from the user. Other devices, systems and methods are also disclosed.

Abstract: In a system (10) for adding speech recognition capabilities to Java, there is provided a speech recognition server (18) coupled to a Java application (24) through an application program interface (20). The Java application (24) dynamically specifies a grammar (56) to the application program interface (20), which communicates the grammar (56) to the speech recognition server (18). The speech recognition server (18) receives the grammar (56) and a speech input (66). Upon receiving the speech input (66), the speech recognition server (18) performs speech recognition and generates a result (58) based on the grammar (56). The application program interface (20) communicates the result (58) to the Java application (24), which performs an action based on the result (58) received.

Abstract: A text-to-pronunciation system (11) includes a large training set of word pronunciations (19) and an extractor for extracting language specific information from the training set to produce pronunciations for words not in its training set. A learner (13) forms pronunciation guesses for words in the training set and for finding a transformation rule that improves the guesses. A rule applier (15) applies the transformation rule found to guesses. The learner (13) repeats the finding of another rule and the rule applier (15) applies the new rule to find the rules that improves the guesses the most.

Abstract: This is a voice activated Hypermedia system using grammatical metadata, the system comprising: a speech user agent; a browsing module; and an information resource. The system may include: embedded intelligence in hypermedia source; a means for processing the actions of a user based on the embedded intelligence; a means for returning a result of the actions to the user. In addition, the hypermedia source maybe a HTML page or an instructional module for communicating allowed actions by a user. The system may also include embedded intelligence as a grammar or reference to a grammar. The grammar may be dynamically added to a speech recognizer. In addition, the actions can come from a speech recognizer. Furthermore, the system may include voice activated hypermedia links and intelligent modules that process information from the information resources for allowing actions from the user. Other devices, systems and methods are also disclosed.

Abstract: Enhancement of hypertext pages containing graphical images is provided by extracting 102 the ALT tag from the markup language to support selection of the corresponding hypertext link by uttering the ALT tag phrase. We describe how to add a speakable phrase for images without ALT tags. The approach also applies to client image maps that can include ALT tags for individual areas. The steps include parsing to extract possible BASE tags reference and client map (MAP tag) 102, retaining any BASE tag for relative references or, if missing, creating one using the original page reference (103) and for each anchor (A tag) containing a page reference (HREF) but without link text, and using the ALT tag text as the link text (104). In the case of a missing ALT tag, creating unique link text.

Abstract: A hand-held wireless voice-activated device (10) for controlling a host system (11), such as a computer connected to the World Wide Web. The device (10) has a display (10a), a microphone (10b), and a wireless transmitter (10g) and receiver (10h). It may also have a processor (10e) and memory (10f) for performing voice recognition. A device (20) can be specifically designed for Web browsing, by having a processor (20e) and memory (20f) that perform both voice recognition and interpretation of results of the voice recognition.

Abstract: This is a speech recognition method for modeling adjacent word context, comprising: dividing a first word or period of silence into two portions; dividing a second word or period of silence, adjacent to the first word, into two potions; and combining last portion of the first word or period of silence and first portion of the second word or period of silence to make an acoustic model. The method includes constructing a grammar to restrict the acoustic models to the middle-to-middle context.

Abstract: This is an automated speech recognition system, the system comprising: an input device for receiving voice signals; a means for computing the voice signals into stochastic RGDAGs and individual grammars; a search engine that directly processes the stochastic RGDAGs; a means for adding the individual grammars within the RGDAG; a means for replacing the individual grammars within the RGDAG; and a means for deleting the individual grammars within the RGDAG. The system can include a means for adding modified grammars within RGDAGs; a means for linking a terminal symbol from a first grammar to a start symbol in a second grammar; a means for finding a maximum depth of each symbol in the RGDAG; a means for determining if the system requires parse information for the grammar by looking for ancestor symbols; a means for specifing a plurality of RGs within the RGDAGs as starting points for the search engine; and a means for returning a parse through each of a plurality of RGs in the RGDAGs for a recognized utterance.

Abstract: A method and system are provided for time aligning speech. Speech data is input representing speech signals from a speaker. An orthographic transcription is input including a plurality of words transcribed from the speech signals. A sentence model is generated indicating a selected order of the words in response to the orthographic transcription. In response to the orthographic transcription, word models are generated associated with respective ones of the words. The orthographic transcription is aligned with the speech data in response to the sentence model, to the word models and to the speech data.

Abstract: A speech system recognizes words from a spoken phrase that conform to checksum constraints. Grammar rules are applied to hypothesize words according to the checksum constraints. The checksum associated with the phrase is thus inherent in the grammar. Sentences which do not meet a predetermined checksum constraint are not valid under the grammar rules and are therefore inherently rejected. The checksum constraints result in increased recognition accuracy.

Abstract: A grammar learning aid is implemented with a processor and read only memory programmed in a manner that minimizes memory space and maximizes effective teaching. The programming is based on a unification grammar, in which sentences are determined by their features. The programming is implemented with logic programming in which predicates represent data, and in which logic variables permit features to be unified. This feature-based grammar approach permits an erroneous answer to be associated with a feature and that feature used to generate a similar device.

Abstract: A method for parsing for natural languages includes a grammar and a lexicon. A knowledge base may be used to define elements in the lexicon. A processor receives single words input by a user and adds them to a sentence under construction. Valid next words are predicted after each received input word. The preferred system has two major components: a parser and a predictor. The predictor accesses only the lexicon and the knowledge base, if one is used, to determine the valid next input words. The parser constructs sentences which are valid according to the grammar out of words accepted by the predictor.

Abstract: A chart parser is disclosed which incorporates rule and observation probabilities with stochastic unification grammars. The parser operates frame synchronously to provide top-down hypotheses and to incorporate observation probabilities as they become available. Because the language model produces multiple explanations of the speech data between frames, the prediction and combination of rules may create cycles in a graph representing the best scores. Score calculation includes the detection of these cycles and propagation of the best scores to the next frame. The algorithm creates no more states than a nonprobilistic chart parser, and remains linear for regular grammars and cubic in the worst case for CFGs. The parser allows a direct integration of statistical speech information and linguistic constraints within the same language model, while the language model permits a generalization of HMM-type models. The efficiency of the parser makes it applicable to multiple levels of a spoken language system (e.g.