3522 results about "Speech input" patented technology

The present invention provides a wireless natural language query system, architecture, and method for processing multimodally-originated queries, including voice and proximity-based queries. The natural language query system includes a Web-enabled device including a speech input module for receiving a voice-based query in natural language form from a user and a location / proximity module for receiving location / proximity information from a location / proximity device. The natural language query system also includes a speech conversion module for converting the voice-based query in natural language form to text in natural language form and a natural language processing module for converting the text in natural language form to text in searchable form. The natural language query system further includes a semantic engine module for converting the text in searchable form to a formal database query and a database-look-up module for using the formal database query to obtain a result related to the voice-based query in natural language form from a database.

An interface for remote human input for reading a database, the interface including an automatic voice question unit for eliciting speech input, a speech recognition unit for recognizing human speech input, and a data recognition unit for recognizing remote data input. The interface is associated with a database to search the database using the recognized input. A typical application is as an automated directory enquiry service.

The present invention provides a natural language query system and method for processing and analyzing multimodally-originated queries, including voice and proximity-based queries. The natural language query system includes a Web-enabled device including a speech input module for receiving a voice-based query in natural language form from a user and a location / proximity module for receiving location / proximity information from a location / proximity device. The query system also includes a speech conversion module for converting the voice-based query in natural language form to text in natural language form and a natural language processing module for converting the text in natural language form to text in searchable form. The query system further includes a semantic engine module for converting the text in searchable form to a formal database query and a database-look-up module for using the formal database query to obtain a result related to the voice-based query in natural language form from a database.

Methods, systems, and computer readable storage medium related to operating an intelligent digital assistant are disclosed. A user request is received, the user request including at least a speech input received from a user. The user request including the speech input is processed to obtain a representation of user intent for identifying items of a selection domain based on at least one selection criterion. A prompt is provided to the user, the prompt presenting two or more properties relevant to items of the selection domain and requesting the user to specify relative importance between the two or more properties. A listing of search results is provided to the user, where the listing of search results has been obtained based on the at least one selection criterion and the relative importance provided by the user.

In embodiments of the present invention, a system and computer-implemented method for enabling a user to interact with a mobile device using a voice command may include the steps of defining a structured grammar for generating a global voice command, defining a global voice command of the structured grammar, wherein the global voice command enables access to an object of the mobile device using a single command, and mapping at least one function of the object to the global voice command, wherein upon receiving voice input from the user of the mobile device, the object recognizes the global voice command and controls the function.

Methods, systems, and computer readable storage medium related to operating an intelligent digital assistant are disclosed. A user request is received, the user request including at least a speech input received from a user. Two or more alternative interpretations of user intent are obtained based on the received user request. One or more commonalities and one or more differences among the two or more alternative interpretations of user intent are identified. A response is provided to the user, the response presenting at least one of the identified differences and eliciting additional user input to choose among the two or more alternative interpretations of user intent based on the at least one difference.

A hybrid approach to improve handwriting recognition and voice recognition in data process systems is disclosed. In one embodiment, a front end is used to recognize strokes, characters and / or phonemes. The front end returns candidates with relative or absolute probabilities of matching to the input. Based on linguistic characteristics of the language, e.g. alphabetical or ideographic language for the words being entered, e.g. frequency of words and phrases being used, likely part of speech of the word entered, the morphology of the language, or the context in which the word is entered), a back end combines the candidates determined by the front end from inputs for words to match with known words and the probabilities of the use of such words in the current context.

A virtual vocabulary database is provided for use with a with a particular user database as part of a speech recognition system. Vocabulary elements within the virtual database are imported from the user database and are tagged to include numerical data corresponding to the historical use of the vocabulary element within the user database. For each speech input, potential vocabulary element matches from the speech recognition system are provided to the virtual database software which creates virtual sub-vocabularies from the criteria according to predefined criteria templates. The software then applies vocabulary element weighting adjustments according to the virtual sub-vocabulary weightings and applies the adjustment to the default weighting provided by the speech recognition system. The modified weightings are returned with the associated vocabulary elements to the speech engine for selection of an appropriate match to the input speech.

Architecture for correcting incorrect recognition results in an Asian language speech recognition system. A spelling mode can be launched in response to receiving speech input, the spelling mode for correcting incorrect spelling of the recognition results or generating new words. Correction can be obtained using speech and / or manual selection and entry. The architecture facilitates correction in a single pass, rather than multiples times as in conventional systems. Words corrected using the spelling mode are corrected as a unit and treated as a word. The spelling mode applies to languages of at least the Asian continent, such as Simplified Chinese, Traditional Chinese, and / or other Asian languages such as Japanese.

A computer-implemented method for providing a candidate list of alternatives for a text selection containing text from multiple input sources, each of which can be stochastic (such as a speech recognition unit, handwriting recognition unit, or input method editor) or non-stochastic (such as a keyboard and mouse). A text component of the text selection may be the result of data processed through a series of stochastic input sources, such as speech input that is converted to text by a speech recognition unit before being used as input into an input method editor. To determine alternatives for the text selection, a stochastic input combiner parses the text selection into text components from different input sources. For each stochastic text component, the combiner retrieves a stochastic model containing alternatives for the text component. If the stochastic text component is the result of a series of stochastic input sources, the combiner derives a stochastic model that accurately reflects the probabilities of the results of the entire series. The combiner creates a list of alternatives for the text selection by combining the stochastic models retrieved. The combiner may revise the list of alternatives by applying natural language principles to the text selection as a whole. The list of alternatives for the text selection is then presented to the user. If the user chooses one of the alternatives, then the word processor replaces the text selection with the chosen candidate.

A speech recognition system in which a user may correct a recognition error resulting from speech recognition more efficiently and easily. Speech recognition means compares a plurality of words inputted from speech input means with a plurality of words stored in dictionary means, respectively, and determines a most-competitive word candidate. Word correction means has a word correction function of correcting the words constituting a word sequence displayed on a screen. Competitive word display commanding means selects one or more competitive words having competitive probabilities close to the competitive probability of the most-competitive word candidate and displays the one or more competitive words adjacent to the most-competitive word candidate. Competitive word selection means selects an appropriate correction word from the one or more competitive words. Word replacement commanding means causes one of the most-competitive word candidate to be replaced with the correction word selected by the competitive word selection means.

A natural language dialogue system and a method capable of correcting a speech response are provided. The method includes following steps. A first speech input is received. At least one keyword included in the first speech input is parsed to obtain a candidate list having at least one report answers. One of the report answers is selected from the candidate list as a first report answer, and a first speech response is output according to the first report answer. A second speech input is received and parsed to determine whether the first report answer is correct. If the first report answer is incorrect, another report answer other than the first report answer is selected from the candidate list as a second report answer. According to the second report answer, a second speech response is output.