Abstract: A company may desire to maintain a quality level for messages sent by customer service representatives to customers. The company may receive a message input by a customer service representative, modify the message with one or more neural networks, and transmit the modified message to a customer. To modify a message, an input vector may be created for each word of the message where the input vector is created using a word embedding of the word and a feature vector that represents the characters of the word. The input vectors for the words of the message may be sequentially processed with an encoding neural network to compute a message encoding vector that represents the message. The message encoding vector may then be processed by a decoding neural network to sequentially generate the words of a modified message. The modified message may then be transmitted to the customer.

Abstract: Embodiments of the present invention disclose a method, a computer program product, and a computer system for ranking inclusion and exclusion criteria based on problematic language. A computer receives criteria and identifies semantic entailment between two or more criteria. The computer further identifies inclusionary criteria that appear as exclusionary criteria and exclusionary criteria that is difficult to interpret. The computer additionally identifies criteria having hypothetical, time specific, or complex language. Based on the computer identifying inclusionary criteria that appears as exclusionary criteria, exclusionary criteria that is difficult to interpret, or criteria having hypothetical, time specific, or complex language, the computer ranks the subject criteria based on the identified problematic language and presents the ranked criteria.

Abstract: A method and device for selecting a word to be defined in a mobile communication terminal having an electronic dictionary function. The method includes selecting a word in a displayed text document in response to a first input, displaying the selected word in a search window, searching for the displayed word in response to a request to search for the displayed word, displaying information resulting from the search, and terminating display of the information and displaying the text document.

Abstract: A recurrent neural network (RNN) method implemented on a computer system is used to produce summaries of unstructured text generated by multiple networks of individuals interacting over time by encoding the unstructured text into intermediate representations and decoding the intermediate representations into summaries of each network. Parameter data for the RNN is obtained by using multiple different versions of the same source texts to train the computer system. The method and computer system can be used to identify which of the networks match a query by determining which network generates the query with low or lowest cost.

Abstract: A machine translation system capable of clustering training data and performing dynamic domain adaptation is disclosed. An unsupervised domain clustering process is utilized to identify domains in general training data that can include in-domain training data and out-of-domain training data. Segments in the general training data are then assigned to the domains in order to create domain-specific training data. The domain-specific training data is then utilized to create domain-specific language models, domain-specific translation models, and domain-specific model weights for the domains. An input segment to be translated can be assigned to a domain at translation time. The domain-specific model weights for the assigned domain can be utilized to translate the input segment.

Abstract: The disclosure relates to methods, systems and other embodiments directed to determining an information domain match for a natural language (NL) input (e.g., a spoken utterance), and confirming whether the NL input is correctly matched to the information domain. For example, after receiving an NL input, a first information domain to which the NL input belongs and a feature value set may be determined based on a semantic pattern matching technique. Further, a second information domain to which the NL input belongs, and a corresponding confidence score related to the second information domain may be determined. The second information domain may be determined based on a first statistical classification technique. Based on the determined feature value set and the confidence score related to the second information domain, it may be confirmed whether the NL input correctly belongs to the first information domain, e.g., based on a second statistical classification technique.

Abstract: Client instance data including a plurality of incidents is obtained, each incident including a plurality of fields. A target field and an evaluation field are selected from among the plural fields. The plurality of incidents are grouped into a plurality of clusters based on a degree of a natural language text similarity of respective target fields in the plurality of incidents. A quality value is determined for each of the plurality of clusters based on the degree of the natural language text similarity of respective target fields in grouped incidents of the cluster from among the plurality of incidents, and based on respective evaluation fields. Each of the plurality of clusters is ranked based on the respective quality value of the cluster and a number of the grouped incidents of the cluster. At least one of the ranked plurality of clusters is identified to perform a service management operation.

Abstract: A method may include receiving, by a device, an input sample of textual content. The method may include identifying, by the device, a comparison sample that is semantically similar to the input sample. The comparison sample may be identified based on a similarity score, of the comparison sample and the input sample, satisfying a semantic similarity threshold. The method may include identifying, by the device, a plurality of output samples of textual content based on acceptance information corresponding to the plurality of output samples and the comparison sample. The acceptance information may be determined based on a user input regarding similarity or relevance of the plurality of output samples and the comparison sample, and the user input may be received before the input sample is received.

Abstract: A grammatically diverse test set of natural language sentences for a deep question answering system is provided by analyzing a given sentence to characterize its syntactical classification, and adding the sentence to the test set if its classification is sufficiently different from other sentences already in the test set. A particular sentence may be selected for inclusion according to a desired syntactic distribution. Multiple sentences having the exact same classification may be allowed subject to a maximum number of such sentences. The test set is adapted to an element of interest by characterizing each syntactical classification relative to the element of interest. The analysis derives a parse tree, identifies a particular node of the tree corresponding to the element of interest, and extracts syntactic information by traversing the tree starting at the particular node and ending at the root node of the tree according to different traversal schemes.

Abstract: Systems and method are disclosed for dynamically creating a translated virtual website based on a machine translation of an existing website without adding any code to the source website. In one exemplary embodiment, an extension to a URL is recognized as requesting a translated website, and the request is routed to an MT server. The original-language content is retrieved, translated, and returned to the user system without any further action by the user. In a further exemplary embodiment, a secure connection can be established to enable translation of non-public websites. In a further exemplary embodiment, a crawler can index the translated website. In a further exemplary embodiment, an RSS feed returns translated content.

Abstract: Systems, methods, and computer-readable storage media for providing for intelligent switching of languages and/or pronunciations in a text-to-speech system. As the system receives text, the text is analyzed to identify portions which should have speech constructed using a pronunciation distinct from the remaining portions of the text. The text-to-speech system uses multiple pronunciation dictionaries to generate and produce speech corresponding to the text, where the identified portions of the text are in a different language or have a different accent from the remainder of the text. Having generated speech corresponding to the text in multiple languages, accents, or dialects, the system combines the portions, then communicates the speech to the text recipient.

Abstract: Systems and methods for translating a source segment are disclosed. In embodiments, a computer-implemented method for translating a source segment comprises receiving, by a computing device, the source segment in a first language to be translated into a second language; identifying, by the computing device, linguistic markers within the source segment and associated noise values to produce a tagged source segment, wherein the linguistic markers are associated with one or more linguistic patterns likely to introduce noise into a translation channel; transforming, by the computing device, the tagged source segment into an amplified source segment; and sending, by the computing device, the amplified source segment to a machine translation module, wherein the machine translation module is configured to process the amplified source segment to produce a return amplified match in the second language.

Abstract: Systems and methods for identifying and locating related content using natural language processing are generally disclosed herein. One embodiment includes an HTML5/JavaScript user interface configured to execute scripting commands to perform natural language processing and related content searches, and to provide a dynamic interface that enables both user-interactive and automatic methods of obtaining and displaying related content. The natural language processing may extract one or more context-sensitive key terms of text associated with a set of content. Related content may be located and identified using keyword searches that include the context-sensitive key terms. For example, text associated with video of a first content, such as text originating from subtitles or closed captioning, may be used to perform searches and locate related content such as a video of a second content, or text of a third content.

Abstract: According to one embodiment, an apparatus includes a storage unit, a first acquisition unit, a second acquisition unit, an analyzer, and a recognition unit. The storage unit stores first situation information about a situation assumed in advance, a first representation representing a meaning of a sentence assumed, intention information representing an intention to be estimated, and a first value representing a degree of application of the first representation to the first situation information and the intention information. The first acquisition unit acquires a natural sentence. The second acquisition unit acquires second situation information about a situation when acquiring the natural sentence. The analyzer analyzes the natural sentence and generates a second representation representing a meaning of the natural sentence. The recognition unit obtains an estimated value based on the first value associated with the first situation information and the first representation.

Abstract: A system including a natural language processing interface to configure a user interface of a device to receive an input, understand an intent from the input, and send a second set of instructions to the device to operate the device to configure the user interface to display a feedback request and receive a second input, and a control system to select a model to transform the intent to an action to influence physical conditions of a building, determine a state of one or more components to perform the action, and send instructions to the one or more components to alter their operations to achieve the state.

Abstract: A rendering engine and method for a displaying foreign-text string and its translation in a single, composite-text string so as to reduce eye fatigue and thought interruption associated with eye shift between typical display schemes in which the foreign-text string and its translation are each presented in different fields of vision.

Abstract: The present teaching relates to automatic formality classification and transformation of online text items. In one example, a request is received for transforming a formality level of a text item in an online communication. A current formality level of the text item is obtained. The current formality level represents a current degree of formality of the text item. A target formality level is determined for the text item based on the request. The target formality level represents a targeted degree of formality for the text item. The text item having the current formality level is transformed to a transformed text item having the target formality level. The transformed text item has a same literal meaning as the text item. The transformed text item is provided as a response to the request.

Abstract: Aspects described herein provide quality assurance checks for improving the construction of natural language understanding grammars. An annotation module may obtain a set of annotations for a set of text samples based, at least in part, on an ontology and a grammar. A quality assurance module may automatically perform one or more quality assurance checks on the set of annotations, the ontology, the grammar, or combinations thereof. The quality assurance module may generate a list of flagged annotations during performance of a quality assurance check. The list of flagged annotations may be presented at an annotation review interface displayed at a display device. One of the flagged annotations may be selected and presented at an annotation interface displayed at the display device. Responsive to presentation of the flagged annotation, the ontology, the grammar, the flagged annotation selected, or combinations thereof may be updated based on user input received.

Abstract: A method, system and computer program product for recognizing terms in a specified corpus. In one embodiment, the method comprises providing a set of known terms t?T, each of the known terms t belonging to a set of types ? (t)={?1, . . . }, wherein each of the terms is comprised of a list of words, t=w1, w2, . . . , wn, and the union of all the words for all the terms is a word set W. The method further comprises using the set of terms T and the set of types to determine a set of pattern-to-type mappings p??; and using the set of pattern-to-type mappings to recognize terms in the specified corpus and, for each of the recognized terms in the specified corpus, to recognize one or more of the types ? for said each recognized term.

Abstract: An approach to classify different defect records by mapping plain language phrases to a taxonomy. The approach includes a method that includes receiving, by at least one computing device, a defect record associated with a defect. The method further includes receiving, by the least one computing device, a plain language phrase or word. The method further includes mapping, by the least one computing device, the plain language phrase or word to a taxonomy. The method further includes classifying, by the least one computing device, how the defect was at least one of detected and resolved using the taxonomy.