1786 results about "Grammaticality" patented technology

An ontology-based parser incorporates both a system and method for converting natural-language text into predicate-argument format that can be easily used by a variety of applications, including search engines, summarization applications, categorization applications, and word processors. The ontology-based parser contains functional components for receiving documents in a plurality of formats, tokenizing them into instances of concepts from an ontology, and assembling the resulting concepts into predicates. The ontological parser has two major functional elements, a sentence lexer and a parser. The sentence lexer takes a sentence and converts it into a sequence of ontological entities that are tagged with part-of-speech information. The parser converts the sequence of ontological entities into predicate structures using a two-stage process that analyzes the grammatical structure of the sentence, and then applies rules to it that bind arguments into predicates.

A parser-translator technology allows a user to specify complex test and/or transformation statements in a high-level user language, to ensure that such test and/or transformation statements are well-formed in accordance with a grammar defining legal statements in the user language, and to translate statements defined by the user into logically and syntactically correct directives for performing the desired data transformations or operations. Using the parser-translator technology, a user can focus on the semantics of the desired operations and need not be concerned with the proper syntax of a language for a particular system. Instead, grammars (i.e., data) define the behavior of a parser-translator implementation by encoding the universe of statements (e.g., legal test and/or transformation statements) and by encoding translations appropriate to a particular data processing application (e.g., a data conversion program, etc.). Some parser-translator implementations described herein interface dynamically with other systems and/or repositories to query for information about objects, systems and states represented therein, and/or their respective interfaces. Some grammars described herein encode sensitivity to an external context. In this way, context-sensitive prompting and validation of correct specification of statements is provided. A combination of parser technology and dynamic querying of external system state allows users to build complex statements (e.g., using natural languages within a user interface environment) and to translate those complex statements into statements or directives appropriate to a particular data processing application.

An intelligent home automation system answers questions of a user speaking “natural language” located in a home. The system is connected to, and may carry out the user's commands to control, any circuit, object, or system in the home. The system can answer questions by accessing the Internet. Using a transducer that “hears” human pulses, the system may be able to identify, announce and keep track of anyone entering or staying in the home or participating in a conversation, including announcing their identity in advance. The system may interrupt a conversation to implement specific commands and resume the conversation after implementation. The system may have extensible memory structures for term, phrase, relation and knowledge, question answering routines and a parser analyzer that uses transformational grammar and a modified three hypothesis analysis. The parser analyzer can be dormant unless spoken to. The system has emergency modes for prioritization of commands.

An apparatus and system for analyzing intention are provided. The apparatus for analyzing an intention applies a context-free grammar to each of one or more sentences in units of one or more phrases to perform phrase spotting on each sentence, thereby extending a recognition range for an out-of-grammar (OOG) expression. Meanwhile, the apparatus for analyzing an intention determines whether sentences that have undergone phrase spotting are grammatically valid by applying a dependency grammar to the sentences to filter an invalid sentence, and generates the intention analysis result of a valid sentence, thereby and grammatically and/or semantically verifying a sentence that has undergone speech recognition while extending a speech recognition range.

A speech dialog system wherein a process for automatic control of devices by speech dialog is used applying methods of speech input, speech signal processing and speech recognition, syntatical-grammatical postediting as well as dialog, executive sequencing and interface control, and which is characterized in that syntax and command structures are set during real-time dialog operation; preprocessing, recognition and dialog control are designed for operation in a noise-encumbered environment; no user training is required for recognition of general commands; training of individual users is necessary for recognition of special commands; the input of commands is done in linked form, the number of words used to form a command for speech input being variable; a real-time processing and execution of the speech dialog is established; and the speech input and output is done in the hands-free mode.

A system for retrieval of text includes a processor which identifies grammar rules associated with text fragments of a text string that is retrieved from an associated storage medium, and retrieves text strings from the storage medium which satisfy the grammar rules. A display displays retrieved text strings. A user input device in communication with the processor enables a user to select text fragments of the displayed text strings for generating a query. The processor identifies grammar rules associated with the user-selected text fragments and retrieves text strings from the storage medium which satisfy the grammar rules.

An apparatus and method defines a markup language for accessing data in a database. The markup language is preferably defined in extensible markup language (XML) by creating suitable document type definitions (DTDs), which define the grammar for accessing data in the database using the markup language. A bridge interprets the data request from the client in markup language format, a suitable database query for the database is formulated, and the data is then placed within a document for delivery in markup language format to the user. As new data types are added to the database, corresponding document type definitions (DTDs) may be dynamically generated, allowing a user to access new kinds of data in a database with a software tool that has a user-friendly graphical user interface without having to manually update the software tool for each new data type that is added to the database.

A computer implemented method for automatically processing a data request comprising accessing a voice signal from a caller, determining geographic information associated with the caller from telephone network information associated with a call made by the caller, and retrieving a speech recognition grammar customized to the geographic information associated with the caller. The method further includes recognizing the voice signal by matching the voice signal to an entry of the speech recognition grammar and providing a directory listing to the caller based on the entry of the speech recognition grammar. The selected grammar may be customized to bias speech recognition to more frequently recognize cities local to the geographic information.

Methods, apparatus, and products are disclosed for supporting multi-lingual user interaction with a multimodal application, the application including a plurality of VoiceXML dialogs, each dialog characterized by a particular language, supporting multi-lingual user interaction implemented with a plurality of speech engines, each speech engine having a grammar and characterized by a language corresponding to one of the dialogs, with the application operating on a multimodal device supporting multiple modes of interaction including a voice mode and one or more non-voice modes, the application operatively coupled to the speech engines through a VoiceXML interpreter, the VoiceXML interpreter: receiving a voice utterance from a user; determining in parallel, using the speech engines, recognition results for each dialog in dependence upon the voice utterance and the grammar for each speech engine; administering the recognition results for the dialogs; and selecting a language for user interaction in dependence upon the administered recognition results.

A speech understanding system includes a language model comprising a combination of an N-gram language model and a context-free grammar language model. The language model stores information related to words and semantic information to be recognized. A module is adapted to receive input from a user and capture the input for processing. The module is further adapted to receive SALT application program interfaces pertaining to recognition of the input. The module is configured to process the SALT application program interfaces and the input to ascertain semantic information pertaining to a first portion of the input and output a semantic object comprising text and semantic information for the first portion by accessing the language model, wherein performing recognition and outputting the semantic object are performed while capturing continues for subsequent portions of the input.

A knowledge-based natural speech dialogue system includes: (i) a knowledge support system, (ii) a flexible dialogue control system, and (iii) a context information system. Flexibilities of the conversation structure, inherent in mixed-initiative mode for dealing with complex user request, are managed because the knowledge structures involved are represented by additional, powerful knowledge representation tools, and because the context information is retained by more specific data structures, which covers larger temporal scopes by the logic of the conversation, rather than by a fixed locality of the grammar flow. This system provides a simple yet reliable method to compensate for these factors to enable more powerful conversation engines with mixed-initiative capabilities.

Improved techniques are disclosed for permitting a user to employ more human-based grammar (i.e., free form or conversational input) while addressing a target system via a voice system. For example, a technique for determining intent associated with a spoken utterance of a user comprises the following steps/operations. Decoded speech uttered by the user is obtained. An intent is then extracted from the decoded speech uttered by the user. The intent is extracted in an iterative manner such that a first class is determined after a first iteration and a sub-class of the first class is determined after a second iteration. The first class and the sub-class of the first class are hierarchically indicative of the intent of the user, e.g., a target and data that may be associated with the target. The multi-stage intent extraction approach may have more than two iterations. By way of example only, the user intent extracting step may further determine a sub-class of the sub-class of the first class after a third iteration, such that the first class, the sub-class of the first class, and the sub-class of the sub-class of the first class are hierarchically indicative of the intent of the user.

Apparatus with accompanying subsystems and methods for developing conversational computer applications. As a user interface, the apparatus allows for a user to initiate the conversation. The apparatus also answers simple and complex questions, understands complex requests, pursues the user for further information when the request is incomplete, and in general provides customer support with a human like conversation while, at the same time, it is capable to interact with a company's proprietary database. As a development tool, the apparatus allows a software developer to implement a conversational system much faster than takes, with current commercial systems to implement basic dialog flows. The apparatus contains three major subsystems: a state transition inference engine, a heuristic answer engine and a parser generator with semantic augmentations. A main process broker controls the flow and the interaction between the different subsystems. The state transition inference engine handles requests that require processing a transaction or retrieving exact information. The heuristic answer engine answers questions that do not require exact answers but enough information to fulfill the user's request. The parser generator processes the user's natural language request, that is, it processes the syntactical structure of the natural language requests and it builds a conceptual structure of the request. After the parser generator processes the user's request, a main process broker feeds the conceptual structure to either the heuristic answer engine or to the state transition inference engine. The interaction between the main process broker and the subsystems creates a conversational environment between the user and the apparatus, while the apparatus uses information from proprietary databases to provide information, or process information, during the course of the conversation. The apparatus is equipped with a programming interface that allows implementers to declare and specify transactions based requests and answers to a multiplicity of questions. The apparatus may be used with a speech recognition interface, in which case, the apparatus improves the recognition results through the context implicitly created by the apparatus.

An enhanced system for speech interpretation is provided. The system may include receiving a user verbalization and generating one or more preliminary interpretations of the verbalization by identifying one or more phonemes in the verbalization. An acoustic grammar may be used to map the phonemes to syllables or words, and the acoustic grammar may include one or more linking elements to reduce a search space associated with the grammar. The preliminary interpretations may be subject to various post-processing techniques to sharpen accuracy of the preliminary interpretation. A heuristic model may assign weights to various parameters based on a context, a user profile, or other domain knowledge. A probable interpretation may be identified based on a confidence score for each of a set of candidate interpretations generated by the heuristic model. The model may be augmented or updated based on various information associated with the interpretation of the verbalization.

A voice browser dialog enabler for multimodal dialog uses a multimodal markup document with fields have markup-based forms associated with each field and defining fragments. A voice browser driver resides on a communication device and provides the fragments and identifiers that identify the fragments. A voice browser implementation resides on a remote voice server and receives the fragments from the driver and downloads a plurality of speech grammars. Input speech is matched against those speech grammars associated with the corresponding identifiers received in a recognition request from the voice browser driver.

A system and method are provided for improved speech synthesis, wherein text data is pre-processed according to updated grammar rules or a selected group of grammar rules. In one embodiment, the TTS system comprises a first memory adapted to store a text information database, a second memory adapted to store grammar rules, and a receiver adapted to receive update data regarding the grammar rules. The system also includes a TTS engine adapted to retrieve at least one text entry from the text information database, pre-process the at least one text entry by applying the updated grammar rules to the at least one text entry, and generate speech based at least in part on the least one pre-processed text entry.

In the present invention, a textual document is syntactically analyzed and knowledge is constructed from a single word or plural words. The knowledge is then marked, from the broken down knowledge (represented by the underscores in FIG. 1) or from a part-of-speech, as a related object (node) or a relation (edge) (represented by ‘n’ or ‘e’ shown in FIG. 1). In other words, in the present invention a textual document is treated as knowledge constructed from a single word or plural words. The knowledge extracted from the textual document is structured to form a knowledge structure (such as a graph structure constituted from nodes and edges). At least one link can be established between each of the knowledge structure elements and a semantically closest concept entry in a hierarchical concept dictionary.

The invention enables creation of grammar networks that can regulate, control, and define the content and scope of human-machine interaction in natural language voice user interfaces (NLVUI). More specifically, the invention concerns a phrase-based modeling of generic structures of verbal interaction and use of these models for the purpose of automating part of the design of such grammar networks.

A speech recognition method includes the steps of receiving input speech containing vocabulary, processing the input speech with a grammar to obtain N-best hypotheses and associated parameter values, and determining whether a first-best hypothesis of the N-best hypotheses is confusable with any vocabulary within the grammar. The first-best hypothesis is accepted as recognized speech corresponding to the received input speech if the first-best hypothesis is not determined to be confusable with any vocabulary within the grammar. Where the first-best hypothesis is determined to be confusable, at least one parameter value of the first-best hypothesis can be compared to at least one threshold value. The first-best hypothesis can be accepted as recognized speech corresponding to the received input speech, if the parameter value of the first-best hypothesis is greater than the threshold value.