Abstract: A collaborative language translation system, computer readable storage medium, and method is disclosed that allocates as between automated and manual language translation services, wherein a manual language translator creates a unique database including manual translator languages capability, accuracy skill level, scope of translation project desired, and translation turnaround time. Also a client creates a unique information set that includes original language, desired language, scope of translated material, client desired translation formats, client desired translation timing, and client desired translation accuracy. Also included in the system is an automated language translation database and instructions for allocating a flow of the unique information set as between the unique database and the automated language translation database based upon the client unique information set and instructions to perform the selected language translation for the client.

Abstract: A system with a nonstatistical translation component integrated with a statistical translation component engine. The same corpus may be used for training the statistical engine and also for determining when to use the statistical engine and when to use the translation component. This training may use probabilistic techniques. Both the statistical engine and the translation components may be capable of translating the same information, however the system determines which component to use based on the training. Retraining can be carried out to add additional components, or when after additional translator training.

Abstract: A syntax analysis information generation apparatus includes an information generation unit. The information generation unit extracts grammatical information corresponding to a word candidate for an analysis target from first syntax analysis information (for example, syntax analysis information for translation) that represents grammatical constraint conditions, and generates second syntax analysis information (for example, syntax analysis information for character recognition) that represents the grammatical constraint conditions corresponding to the word candidate based on the extracted grammatical information.

Abstract: A system and related method for the electronic processing of text onto a two-dimensional coordinate system to analyze the attitudinal mindset associated with the text. The system and related method may also be employed to generate text based on a desired attitudinal mindset to impart. The system includes a computer system embodying functions that enable a user to analyze the text. The system includes one or more functions to parse attitudinal words and objective words and associate two-dimensional coordinates with the subjective words. The system further includes one or more functions for mapping the associated two-dimensional coordinates to show the geographic locations of each attitudinal word of the text in relation to each other attitudinal word of the text. The system decomposes attitudinal words into attitudinal equivalence and reference category and enables the generation of a report of the mindset associated with the analyzed text.

Abstract: A translation and teaching system for sending text messages over a telecommunication pathway sent by users in a first language received by a server, a comparison database of a second language for matching, converting the text into a second language upon making the match, a translator for converting the first text transmission into the second language if no match is made into a second transmission, a processor in the server for analyzing the conversion of the transmission for accuracy, and a data path to send the transmission to the user. The system may have a pre-processor that recognizes linguistic irregularities and modifies them to conform to the second language's pre-stored standard grammar and a human linguist platform for post verification of the translation. The system also generates learning lessons for user in language, a learning dictionary that groves with user input, and the addition of third party content for lessons.

Abstract: A method, including presenting, by a computer system executing a non-tactile three dimensional user interface, a virtual keyboard on a display, the virtual keyboard including multiple virtual keys, and capturing a sequence of depth maps over time of a body part of a human subject. On the display, a cursor is presented at positions indicated by the body part in the captured sequence of depth maps, and one of the multiple virtual keys is selected in response to an interruption of a motion of the presented cursor in proximity to the one of the multiple virtual keys.

Abstract: Appropriate processing results or appropriate apparatuses can be selected with a control device that selects the most probable speech recognition result by using speech recognition scores received with speech recognition results from two or more speech recognition apparatuses; sends the selected speech recognition result to two or more translation apparatuses respectively; selects the most probable translation result by using translation scores received with translation results from the two or more translation apparatuses; sends the selected translation result to two or more speech synthesis apparatuses respectively; receives a speech synthesis processing result including a speech synthesis result and a speech synthesis score from each of the two or more speech synthesis apparatuses; selects the most probable speech synthesis result by using the scores; and sends the selected speech synthesis result to a second terminal apparatus.

Abstract: A method includes accessing text that includes a plurality of words, tagging each of the plurality of words with one of a plurality of parts of speech (POS) tags, and creating a plurality of tokens, each token comprising one of the plurality of words and its associated POS tag. The method further includes clustering one or more of the created tokens into a chunk of tokens, the one or more tokens clustered into the chunk of tokens based on the POS tags of the one or more tokens, and forming a phrase based on the chunk of tokens, the phrase comprising the words of the one or more tokens clustered into the chunk of tokens.

Abstract: One embodiment of the present invention is an XML application module that processes an XML character stream, which module includes an XML interface module, a parallel bit stream module, a lexical item stream module, a parser and a parsed data receiver. The XML interface module applies the XML character stream as input to the parallel bit stream module and the parser; the parallel bit stream module forms parallel bit streams and applies them as input to the lexical item stream module; the lexical stream module forms lexical item streams and applies them as input to the parser; the parser forms a stream of parsed XML data and applies it as input to the parsed data receiver; and the parsed data receiver processes the stream of parsed XML data. The parsed data receiver may be, for example, a communication module of a portable communication device.

Abstract: A computer-implemented method for data loss prevention may include 1) identifying a network configured with a data loss prevention system including at least one data loss prevention policy directed to textual data expressed in a primary natural language, 2) identifying a textual object subject to a data loss prevention assessment within the network, 3) determining that the textual object includes a textual component that is not expressed in the primary natural language, 4) in response to determining that the textual object includes the textual component, translating the textual component from a secondary natural language that the data loss prevention policy does not recognize into the primary natural language that the data loss prevention policy does recognize, and 5) after translating the textual component into the primary natural language, applying the data loss prevention policy to a modified textual object including the translated textual component.

Abstract: A method for securing electronic transactions includes associating a mobile electronic device with a first user. A first computer system retrievably stores registration data relating to the first user, including a device identifier that is unique to the mobile electronic device. A security application that supports in-application push notifications is installed on the mobile electronic device. The first computer system sends a push notification to the mobile electronic device, the push notification prompting the first user to provide a confirmation reply via a user interface of the security application for activating the mobile electronic device as a security token. The mobile electronic device is activated as a security token for the first user in response to receiving at the first computer system, from the mobile electronic device, the confirmation reply from the first user.

Abstract: A method for a patternized record of a bilingual sentence-pair, for recording a source sentence and a corresponding target sentence onto a record medium in a mapping manner, comprising: recording a source sentence into a first part in the record medium, and recording a target sentence into a second part in the record medium; recording at least one patternized unit in at least one of the first part and the second part; in the patternized unit, a content of a unit in target sentence and information of a corresponding unit in source sentence are recorded in a predetermined format; wherein the patternized unit comprises: a source portion, a target portion, a POS portion, an attribute portion, a portion of serial number of a unit, or any combination thereof; wherein each portion in the patternized unit can be identified automatically by a computer. The translation method and translation system base on the bilingual patternized sentence-pair are also disclosed.

Abstract: A source language sentence is tagged with non-lexical tags, such as part-of-speech tags and is parsed using a lexicalized parser trained in the source language. A target language sentence that is a translation of the source language sentence is tagged with non-lexical labels (e.g., part-of speech tags) and is parsed using a delexicalized parser that has been trained in the source language to produce k-best parses. The best parse is selected based on the parse's alignment with lexicalized parse of the source language sentence. The selected best parse can be used to update the parameter vector of a lexicalized parser for the target language.

Abstract: A computer implemented method of translating source material in a source natural language into a target natural language includes receiving a first data input which is a first part of a sub-segment of a translation of the source material from the source natural language into the target natural language, identifying a selectable target text sub-segment in the target natural language associated with the received first data input, and outputting the selectable target text sub-segment. The selectable target text sub-segment is extracted from a corpus of previously translated text segment pairs, each text segment pair having a source text segment in the source natural language and a corresponding translated text segment in the target natural language.

Abstract: The present technology dynamically generates auto-suggest dictionary data from translation data stored in memory at a server. The auto-suggest dictionary data may be transmitted to a remote device by the server for use in language translation. The auto-suggest dictionary data may be transferred as part of a package which includes content to be translated, translation meta-data, and various other data. The auto-suggest dictionary data may be generated at a first computing device, periodically or in response to an event, from translation data stored in memory. The auto-suggest dictionary may be transferred to a remote device along with content to be translated and other data, as part of a package, for use in translation of the content at the remote device.

Abstract: Techniques for interactively presenting word-alignments of multilingual translations and automatically improving those translations based upon user feedback are described herein. With one or more implementations of the techniques described herein, a word-alignment user-interface (UI) concurrently displays a pair of bilingual sentences, where one is a translation of the other, and interactively highlights linked (i.e., “word-aligned”) words and phrases of the pair. Other implementations of the techniques described herein offer an option for a user to provide feedback about the existing word-alignments or realign the words or phrases. In still other described implementations, word-alignment is automatically improved based upon that user feedback.

Abstract: In a machine-translation apparatus, an example storage unit stores therein target language examples in a target language and source language examples in a source language, while keeping the target language examples and the source language examples in correspondence with one another. An input receiving unit receives an input sentence in the source language. A searching unit conducts a search in the example storage unit for one of the target language examples corresponding to one of the source language examples that either matches or is similar to the input sentence. A translating unit generates a reverse-translated sentence by translating the one of the target language examples found in the search into the source language. A detecting unit detects a difference portion between the reverse-translated sentence and the input sentence. An output unit outputs the difference portion.

Abstract: An expression, for which complementary information can be outputted, is extracted from a document obtained by character recognition for an image. Complementary information related to the extracted expression is outputted when a character or a symbol adjacent to the beginning or the end of the extracted expression is not a predetermined character or symbol. Output of complementary information related to the extracted expression is skipped when the character or symbol adjacent to the beginning or the end of the extracted expression is the predetermined character or symbol. A problem that complementary information unrelated to an original text is outputted is prevented even when a false character recognition occurs.

Abstract: In one embodiment, the invention provides a method for machine translation of a source document in an input language to a target document in an output language, comprising generating translation options corresponding to at least portions of each sentence in the input language; and selecting a translation option for the sentence based on statistics associated with the translation options.

Abstract: Speech recognition of even a speaker who uses a speech recognition system is enabled by using an extended recognition dictionary suited to the speaker without requiring any previous learning using an utterance label corresponding to the speech of the speaker.

Abstract: According to example configurations, a speech-processing system parses an uttered sentence into segments. The speech-processing system translates each of the segments in the uttered sentence into candidate textual expressions (i.e., phrases of one or more words) in a first language. The uttered sentence can include multiple phrases or candidate textual expressions. Additionally, the speech-processing system translates each of the candidate textual expressions into candidate textual phrases in a second language. Based at least in part on a product of confidence values associated with the candidate textual expressions in the first language and confidence values associated with the candidate textual phrases in the second language, the speech-processing system produces a confidence metric for each of the candidate textual phrases in the second language.

Abstract: A computer-assisted language correction system including spelling correction functionality, misused word correction functionality, grammar correction functionality and vocabulary enhancement functionality utilizing contextual feature-sequence functionality employing an internet corpus.

Abstract: Computing functionality converts an input linguistic item into a normalized linguistic item, representing a normalized counterpart of the input linguistic item. In one environment, the input linguistic item corresponds to a complaint by a person receiving medical care, and the normalized linguistic item corresponds to a definitive and error-free version of that complaint. In operation, the computing functionality uses plural reference resources to expand the input linguistic item, creating an expanded linguistic item. The computing functionality then forms a graph based on candidate tokens that appear in the expanded linguistic item, and then finds a shortest path through the graph; that path corresponds to the normalized linguistic item. The computing functionality may use a statistical language model to assign weights to edges in the graph, and to determine whether the normalized linguistic incorporates two or more component linguistic items.

Abstract: A bilingual information retrieval apparatus includes an input text acquisition unit, a first memory, a first language construct information selection unit, a second memory, and a second language construct information selection unit. The input text acquisition unit acquires input text in a first language. The first memory stores plural pieces of first language construct information indicating a construct of text in the first language. The first language construct information selection unit selects a piece of first language construct information corresponding to the input text. The second memory stores plural pieces of second language construct information indicating a construct of text in a second language corresponding to the selected piece of first language construct information. The second language construct information selection unit selects a piece of second language construct information on the basis of evaluation information.

Abstract: A method, an apparatus and an article of manufacture for determining a dropped pronoun from a source language. The method includes collecting parallel sentences from a source and a target language, creating at least one word alignment between the parallel sentences in the source and the target language, mapping at least one pronoun from the target language sentence onto the source language sentence, computing at least one feature from the mapping, wherein the at least one feature is extracted from both the source language and the at least one pronoun projected from the target language, and using the at least one feature to train a classifier to predict position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language.

Abstract: A system and method for providing an easy-to-use interface for verifying semantic tags in a steering application in order to generate a natural language grammar. The method includes obtaining user responses to open-ended steering questions, automatically grouping the user responses into groups based on their semantic meaning, and automatically assigning preliminary semantic tags to each of the groups. The user interface enables the user to validate the content of the groups to ensure that all responses within a group have the same semantic meaning and to add or edit semantic tags associated with the groups. The system and method may be applied to interactive voice response (IVR) systems, as well as customer service systems that can communicate with a user via a text or written interface.

Abstract: A mechanism is provided for accelerating data exchange language parsing. An input data stream is loaded into a first in, first out (FIFO) memory. A tokenization bit corresponding to a next byte to be read is extracted from a FIFO. A determination is made as to whether the tokenization bit corresponding to the next byte to be read from the FIFO indicates a control character or a non-control character located in an associated FIFO memory location in the FIFO. Responsive to the tokenization bit indicating the control character, the control character that causes a state change in a state machine is processed. Responsive to the tokenization bit indicating the non-control character, a length associated with the tokenized bit is identified and a set of non-control characters that do not cause a state change in the state machine are processed based on the length associated with the tokenized bit.

Abstract: Methods, systems, and computer readable storage medium related to operating an intelligent digital assistant are disclosed. A text string is obtained from a speech input received from a user. The received text string is interpreted to derive a representation of user intent based at least in part on a plurality of words associated with a user and stored in memory associated with the user, the plurality of words including words from a plurality of user interactions with an automated assistant. At least one domain, a task, and at least one parameter for the task, are identified based at least in part on the representation of user intent. The identified task is performed. An output is provided to the user, where the output is related to the performance of the task.

Abstract: Verifying text translation in a program including obtaining a first program integrated information (PII) file and a second PII file of text in the program. An original page is generated by using the first PII file. Document object model (DOM) tree information of the original page is obtained. For each text unit in the original page: identification information corresponding to a first text unit in the first PII file is extracted; a second text unit is identified in the second PII file using the extracted identification information and a relationship between the identification information and the second text unit; and the first text unit is replaced in the DOM tree with the second text unit. A new page is generated using the text units from the second PII file.

Abstract: Example embodiments of the present invention may include a method that provides transcribing spoken utterances occurring during a call and assigning each of the spoken utterances with a corresponding set of first classifications. The method may also include determining a confidence rating associated with each of the spoken utterances and the assigned set of first classifications, and performing at least one of reclassifying the spoken utterances with new classifications based on at least one additional classification operation, and adding the assigned first classifications and the corresponding plurality of spoken utterances to a training data set.

Abstract: Embodiments of the present invention disclose computer-implemented method for generating examples for electronic dictionaries to serve as an aid to translation between languages, comprising: for at least one dictionary entry comprising a headword Wj in a source language and at least one translation Tj1, Tj2, . . . Tjn for the headword Wj in a target language: generating a first set comprising possible forms for the headword Wj in the source language and a second set comprising possible forms for each translation Tj1, Tj2, . . . Tjn in the target language; searching a corpus of translations for at least one translation sentence pair that includes the headword Wj, or one of its generated forms, in a first part of the pair, and a translation Tjn or one of its generated forms, in a second part of the pair; and providing each translation sentence pair to a user.

Abstract: A method and computer system for translating sentences between languages from an intermediate language-independent semantic representation is provided. On the basis of comprehensive understanding about languages and semantics, exhaustive linguistic descriptions are used to analyze sentences, to build syntactic structures and language independent semantic structures and representations, and to synthesize one or more sentences in a natural or artificial language. A computer system is also provided to analyze and synthesize various linguistic structures and to perform translation of a wide spectrum of various sentence types. As result, a generalized data structure, such as a semantic structure, is generated from a sentence of an input language and can be transformed into a natural sentence expressing its meaning correctly in an output language.

Abstract: A system and method for capitalizing translated text is provided. A capitalized source text is automatically translated to a target text. The target text is capitalized according to information in the capitalized source text.

Abstract: Systems and methods for enhancing machine translation post edit review processes are provided herein. According to some embodiments, methods for displaying confidence estimations for machine translated segments of a source document may include executing instructions stored in memory, the instructions being executed by a processor to calculate a confidence estimation for a machine translated segment of a source document, compare the confidence estimation for the machine translated segment to one or more benchmark values, associate the machine translated segment with a color based upon the confidence estimation for the machine translated segment relative to the one or more benchmark values, and provide the machine translated segment having the color in a graphical format, to a client device.

Abstract: Disclosed are systems, methods, and computer-readable media for performing translations from a source language to a target language. The method comprises receiving a source phrase, generating a target bag of words based on a global lexical selection of words that loosely couples the source words/phrases and target words/phrases, and reconstructing a target phrase or sentence by considering all permutations of words with a conditional probability greater than a threshold.

Abstract: Embodiments provide caller information in multiple languages to multiple receiving communication devices. In one embodiment, the method includes receiving a call request from a sending endpoint communication device connected to a network. Caller identification information associated with the call request is obtained, where the caller identification information includes one or more identifications associated with the sending endpoint communication device. Each identification specifies the same content in a different language. The call request and at least one of the identifications are transmitted over the network to be received by receiving endpoint communication devices connected to the network. Each receiving endpoint communication device can output at least one of the received identifications specified in a language designated for use by that receiving endpoint communication device.

Abstract: A method, computer program product and system are disclosed for determining the semantic density of textualized digital media (a measure of how much information is conveyed in a sentence or clause relative to its length). The more semantically dense text is, the more information it conveys in a given space. Users input a topic, a timeline, and one or more target web media sources for analysis. Text in the target media sources is deconstructed to determine density, and a density rating assigned to the web media source. Over time, users can track trends in the density of text media relative to a given topic, and determine how much information is being conveyed in connection with the topic, such as a political campaign. Line graphs, pie charts, and other time-elapsed output graphic representations of the semantic density are generated and rendered for the user.

Abstract: The method and apparatus for discriminative natural language parsing, uses a deep convolutional neural network adapted for text and a structured tag inference in a graph. In the method and apparatus, a trained recursive convolutional graph transformer network, formed by the deep convolutional neural network and the graph, predicts “levels” of a parse tree based on predictions of previous levels.

Abstract: A method of translating a computer generated log output message from a first language to a second language, including receiving a log output containing a plurality of messages in a first language and matching words and phrases in the log output messages to pre-established codes in a matched message index. Ambiguous matches are resolved by removing codes matched to ones of the words and phrases that have overlap with words and phrases matched to different codes. The codes in the matched message index are translated into a second language different than the first language to a corresponding second log output message in the second language and then the second log output message is output in the second language.

Abstract: Methods, systems and program product are disclosed for determining matching level of a text lookup segment with a plurality of source texts in a translation memory in terms of context. The invention determines exact matches for the lookup segment in the plurality of source texts, and determines, in the case that at least one exact match is determined, that a respective exact match is an in-context exact match for the lookup segment in the case that a context of the lookup segment matches that of the respective exact match. Degree of context matching required can be predetermined, and results prioritized. The invention also includes methods, systems and program products for storing a translation pair of source text and target text in a translation memory including context, and the translation memory so formed. The invention ensures that content is translated the same as previously translated content and reduces translator intervention.

Abstract: A method and system for presenting choices of different translations of a message and corresponding interpretations of the different translations. The message that is input by a sender to be sent to an intended recipient is received. Choices of the different translations of the message and different corresponding interpretations of the different translations are retrieved and presented. The different translations are in a language understood by the recipient. The different interpretations are specific to a culture of the recipient. A selection of a translation of the different translations is received. The selection of the translation is based on a review of the different interpretations by the sender. The selected translation is presented to the recipient.

Abstract: Computer-implemented systems and methods are provided for identifying language that would be considered obscene or otherwise offensive to a user or proprietor of a system. A first plurality of offensive words are received, and a second plurality of offensive words are received. A string of words are received, where one or more detected offensive words are selected from the string of words that matches words from the first plurality of offensive words or the second plurality of offensive words. The string of words is processed based upon the detection of offensive words in the string of words.

Abstract: A recognition dictionary creation device identifies the language of a reading of an inputted text which is a target to be registered and adds a reading with phonemes in the language identified thereby to the target text to be registered, and also converts the reading of the target text to be registered from the phonemes in the language identified thereby to phonemes in a language to be recognized which is handled in voice recognition to create a recognition dictionary in which the converted reading of the target text to be registered is registered.

Abstract: Information extraction and annotation systems and methods for use in annotating and determining annotation instances are provided herein. Exemplary methods include receiving annotated documents, the annotated documents comprising annotated fields, analyzing the annotated documents to determine contextual information for each of the annotated fields, determining discriminative sequences using the contextual information, generating a proposed rule or a feature set using the discriminative sequences and annotated fields, and providing the proposed rule or the feature set to a document annotator.

Abstract: Systems, methods, and apparatuses including computer program products for machine translation. A method is provided that includes generating a plurality of machine translation systems using a single machine translation engine, and generating a consensus translation from a plurality of candidate translations for a source sentence, where each candidate translation of the plurality of candidate translations is an output of a respective machine translation system of the plurality of machine translation systems.

Abstract: Provided are techniques for parsing a name. A name to be parsed is received. A culture of the name is identified. One or more name phrases from the name are identified. Statistics for the one or more name phrases are identified. It is determined whether to perform a first parsing technique that parses different types of name elements within at least one field of the name. In response to determining that the first parsing technique is to be performed, the name is parsed using the statistics and the first parsing technique. In response to determining that the first parsing technique is not to be performed, the name is parsed using the statistics and a second parsing technique.

Abstract: A computer-implemented method of translating text from a source language to a target language includes the steps of (a) detecting a source language on a first communication device, (b) detecting a location of the first communication device, (c) determining the target language based upon the detected location of the first communication device, (d) receiving an input for translation from the first communication device, (e) displaying a list of popular source phrases that are similar to the received input on the first communication device, (f) translating a user selected similar popular source phrase if the user selects the similar popular source phrase, else translating the input by means of a machine translation engine, and (g) displaying the translation output of the user selected similar popular source phrase if the user selected the similar popular source phrase, else determining if the translation output from the machine translation engine has been approved by a human translator, submitting the translation

Abstract: Disclosed are various embodiments for client-side internationalization of network pages. A network page and code that localizes the network page are obtained from a server. The code that localizes the network page is executed in a client and determines a locale associated with the client. One or more internationalized elements are identified in the network page. The internationalized elements are replaced with corresponding localized translations. The network page is rendered for display in the client after the network page has been localized.

Abstract: Techniques disclosed herein include systems and methods for creating a bootstrap call router for other languages by using selected N-best translations. Techniques include using N-best translations from a machine translation system so as to increase a possibility that desired keywords in a target language are covered in the machine translation output. A 1-best translation is added to a new text corpus. This is followed by selecting a subset that provides a varied set of translations for a given source transcribed utterance for better translation coverage. Additional translations are added to the new text corpus based on a measure of possible translations having words not yet seen for the selected transcribed utterances, and also based on possible translation having words that are not associated with very many or semantic tags in the new text corpus. Candidate translations can be selected from a window of N-best translations calculated based on machine translation accuracy.

Abstract: A user input is received by a computing device. An interactive input module determines whether the first user input is a first character of a script for a supported language. If the first user input is a first character, the first character is stored in an input buffer. A plurality of words in the supported language that match a contents of the input buffer are identified, and a subset of the plurality of words are displayed to the user based on a frequency value associated with each of the plurality of words.