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5047 results about "Spoken Language Ability" patented technology

Spoken language relies on human physical ability to produce sound, which is a longitudinal wave propagated through the air at a frequency capable of vibrating the ear drum. This ability depends on the physiology of the human speech organs.

Parser translator system and method

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.
Owner:VERSATA

Distributed real time speech recognition system

InactiveUS20050080625A1Facilitates query recognitionAccurate best responseNatural language translationData processing applicationsFull text searchTime system
A real-time system incorporating speech recognition and linguistic processing for recognizing a spoken query by a user and distributed between client and server, is disclosed. The system accepts user's queries in the form of speech at the client where minimal processing extracts a sufficient number of acoustic speech vectors representing the utterance. These vectors are sent via a communications channel to the server where additional acoustic vectors are derived. Using Hidden Markov Models (HMMs), and appropriate grammars and dictionaries conditioned by the selections made by the user, the speech representing the user's query is fully decoded into text (or some other suitable form) at the server. This text corresponding to the user's query is then simultaneously sent to a natural language engine and a database processor where optimized SQL statements are constructed for a full-text search from a database for a recordset of several stored questions that best matches the user's query. Further processing in the natural language engine narrows the search to a single stored question. The answer corresponding to this single stored question is next retrieved from the file path and sent to the client in compressed form. At the client, the answer to the user's query is articulated to the user using a text-to-speech engine in his or her native natural language. The system requires no training and can operate in several natural languages.
Owner:NUANCE COMM INC

Method and system for automatically extracting relations between concepts included in text

A method and system for automatically extracting relations between concepts included in electronic text is described. Aspects the exemplary embodiment include a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets. The semantic network further includes semantic information comprising at least one of: 1) an expanded set of semantic relation links representing: hierarchical semantic relations, synset / corpus semantic relations verb / subject semantic relations, verb / direct object semantic relations, and fine grain / coarse grain semantic relationship; 2) a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and 3) a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language. A linguistic engine uses the semantic network to performing semantic disambiguation on the electronic text using one or more of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference.
Owner:EXPERT AI SPA

Virtual keyboard system with automatic correction

There is disclosed an enhanced text entry system which uses word-level analysis to correct inaccuracies automatically in user keystroke entries on reduced-size or virtual keyboards. A method and system are defined which determine one or more alternate textual interpretations of each sequence of inputs detected within a designated auto-correcting region. The actual interaction locations for the keystrokes may occur outside the boundaries of the specific keyboard key regions associated with the actual characters of the word interpretations proposed or offered for selection, where the distance from each interaction location to each corresponding intended character may in general increase with the expected frequency of the intended word in the language or in a particular context. Likewise, in a virtual keyboard system, the keys actuated may differ from the keys actually associated with the letters of the word interpretations. Each such sequence corresponds to a complete word, and the user can easily select the intended word from among the generated interpretations. Additionally, when the system cannot identify a sufficient number of likely word interpretation candidates of the same length as the input sequence, candidates are identified whose initial letters correspond to a likely interpretation of the input sequence.
Owner:NUANCE COMM INC +1
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