8043results about "Natural language translation" patented technology

The intelligent automated assistant system engages with the user in an integrated, conversational manner using natural language dialog, and invokes external services when appropriate to obtain information or perform various actions. The system can be implemented using any of a number of different platforms, such as the web, email, smartphone, and the like, or any combination thereof. In one embodiment, the system is based on sets of interrelated domains and tasks, and employs additional functionally powered by external services with which the system can interact.

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.

A method for processing natural language includes receiving an information input string. Referent tridbits corresponding to stimuli in the information input string are generated. Assert tridbits defining relationships between the referent tridbits are generated. A language processing system including a rules database and a meaning engine. The rules database is operable to store a plurality of syntax rules. The meaning engine is operable to receiving an information input string, generate referent tridbits corresponding to stimuli in the information input string based on the syntax rules, and generate assert tridbits defining relationships between the referent tridbits based on the syntax rules.

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 system enables a transcriptionist to replace a first written form (such as an abbreviation) of a concept with a second written form (such as an expanded form) of the same concept. For example, the system may display to the transcriptionist a draft document produced from speech by an automatic speech recognizer. If the transcriptionist recognizes a first written form of a concept that should be replaced with a second written form of the same concept, the transcriptionist may provide the system with a replacement command. In response, the system may identify the second written form of the concept and replace the first written form with the second written form in the draft document.

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.

A method for transliteration includes receiving input such as a word, a sentence, a phrase, and a paragraph, in a source language, creating source language sub-phonetic units for the word and converting the source language sub-phonetic units for the word to target language sub-phonetic units, retrieving ranking for each of the target language sub-phonetic units from a database and creating target language words for the word in the source language based on the target language sub-phonetic units and ranking of the each of the target language sub-phonetic units. The method further includes identifying candidate target language words based predefined criteria, and displaying candidate target language words.

A method for rewriting source text includes receiving source text including a source text string in a first natural language. The source text string is translated with a machine translation system to generate a first target text string in a second natural language. A translation confidence for the source text string is computed, based on the first target text string. At least one alternative text string is generated, where possible, in the first natural language by automatically rewriting the source string. Each alternative string is translated to generate a second target text string in the second natural language. A translation confidence is computed for the alternative text string based on the second target string. Based on the computed translation confidences, one of the alternative text strings may be selected as a candidate replacement for the source text string and may be proposed to a user on a graphical user interface.