Abstract: A method is provided for limiting access to airspace by drones. The method includes receiving position information from a user associated with a property identified by the position information. The method also includes assembling the position information with other position information to compile a comprehensive configurable flight zone database. The method further includes pushing the configurable flight zone database to at least one drone. The drone accesses the configurable flight zone database to determine if movement is allowed, and the drone is programmed to not fly into areas identified in the configurable flight zone database. In the method, the drone may be further programmed to prohibit directing a camera into the areas identified in the configurable flight zone database.

Abstract: A method to induce an immediate psychosomatic change in a patient optimal for a particular medical procedure, is provided. The method uses a brain-computer interface integrating a loop of biofeedback and neurofeedback components, interactive, immersive, 3D virtual reality (VR) modules utilizing hypnotic or guided-response, learning, placebo and experience-ratification principles. The method will differentiate between low and high hypnotizable patients as well their specific abilities and limitations by their distinct brain patterns and will deliver VR output content appropriate for the current and targeted psychosomatic state of the patient, needs, and stage of a particular medical procedure thus being applicable to any medical patient regardless of abilities. The device will continuously measure the patient's physiological markers and will customize the intensity, order, timing, and content of the output “dose.

Abstract: A method is provided for limiting access to airspace by drones. The method includes receiving position information from a user associated with a property identified by the position information. The method also includes assembling the position information with other position information to compile a comprehensive configurable flight zone database. The method further includes pushing the configurable flight zone database to at least one drone. The drone accesses the configurable flight zone database to determine if movement is allowed, and the drone is programmed to not fly into areas identified in the configurable flight zone database. In the method, the drone may be further programmed to prohibit directing a camera into the areas identified in the configurable flight zone database.

Abstract: Personalizing machine translation via online adaptation is described herein. According to some embodiments, methods for providing personalized machine translations may include receiving translator feedback regarding machine translations generated by a machine translation system for a translator, determining translator feedback that improves translations generated by the machine translation system, and incorporating the determined translator feedback into the translation methodology of the machine translation system to personalize the translation methodology.

Abstract: Despite the significantly researched curative properties and health benefits of psychosomatic approaches such as clinical hypnosis and bio- and neurofeedback, they are still broadly underused in medical settings. The delivery of efficient holistic treatment requires organically uniting the mind and body treatment approaches in a well-calibrated, reliable and intensive treatment. We propose a method for reliably achieving the necessary psychosomatic state that is optimal for the specific current needs of medical patients via a medical device utilizing brain-computer interface that integrates immersive, interactive virtual reality with bio- and neurofeedback, and hypnotic or guided-response modules. The method will solve the practical limitations in the utilization of the aforementioned psychosomatic approaches, augmenting their efficacy and permitting their reliable and measurable integration in a medical treatment, optimizing it in terms of efficacy, time, and cost.

Abstract: A document containing text in a source language may be translated into a target language based on content associated with that document, in conjunction with the present technology. An indication to perform an optimal translation of a document into a target language may be received via a user interface. The document may then be accessed by a computing device. The optimal translation is executed by a preferred translation engine of a plurality of available translation engines. The preferred translation engine is the most likely to produce the most accurate translation of the document among the plurality of available translation engines. Additionally, the preferred translation engine may be identified based on content associated with the document. The document is translated into the target language using the preferred translation engine to obtain a translated document, which may then be outputted by a computing device.

Abstract: Systems, computer programs, and methods for identifying parallel documents and/or fragments in a bilingual collection are provided. The method for identifying parallel sub-sentential fragments in a bilingual collection comprises translating a source document from a bilingual collection. The method further includes querying a target library associated with the bilingual collection using the translated source document, and identifying one or more target documents based on the query. Subsequently, a source sentence associated with the source document is aligned to one or more target sentences associated with the one or more target documents. Finally, the method includes determining whether a source fragment associated with the source sentence comprises a parallel translation of a target fragment associated with the one or more target sentences.

Abstract: Systems and methods for generating trust scores for translations are described herein. According to some embodiments, methods for generating a trust score for a translation may include establishing a trust score for at least a portion of a first translation of a source text translated by a trusted translation system, the trust score representing an accuracy level for the first translation, comparing the first translation of the source text generated by the trusted translation system to a second translation of the source text generated by an untrusted translation system, and determining a trust score for the second translation based upon the comparison.

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: Embodiments of the present invention provide a system and method for providing a translation service. The method comprises providing a translation interface accessible via a network. The translation interface receives specialized data associated with a domain from a member. A text string written in a source language is received from the member via the translation interface. A domain-based translation engine is selected. The domain-based translation engine may be associated with a source language, a target language, and a domain. The text string is translated into the target language using, at least in part, the selected domain-based translation engine. The translated text string is transmitted to the member via the Internet. In some embodiments, a translation memory is generated based on the specialized data.

Abstract: The present invention provides a method that includes receiving a result word set in a target language representing a translation of a test word set in a source language. When the result word set is not in a set of acceptable translations, the method includes measuring a minimum number of edits to transform the result word set into a transform word set. The transform word set is in the set of acceptable translations. A system is provided that includes a receiver to receive a result word set and a counter to measure a minimum number of edits to transform the result word set into a transform word set. A method is provided that includes automatically determining a translation ability of a human translator based on a test result. The method also includes adjusting the translation ability of the human translator based on historical data of translations performed by the human translator.

Abstract: Personalizing machine translation via online adaptation is described herein. According to some embodiments, methods for providing personalized machine translations may include receiving translator feedback regarding machine translations generated by a machine translation system for a translator, determining translator feedback that improves translations generated by the machine translation system, and incorporating the determined translator feedback into the translation methodology of the machine translation system to personalize the translation methodology.

Abstract: Customers having a translation project to select a translation method from a variety of options, ranging from a completely human translation to a completely automated translation. For human translations, translation job information may be communicated through one or more network service modules which execute within a network service application, such as a web-based networking application. A network service module may register a user having an account with the network service application as a translator and communicate translation jobs to the user. One or more users who express interest in performing the translation are selected to perform a translation job, each job comprising at least a portion of the translation project. After a user provides a translation for the translation job, the translation is analyzed to generate a trust level prediction for the translation. A user translation profile may be updated after each translation to reflect the user's performance.

Abstract: To automatically annotate an essay, a sentence of the essay is identified and a feature associated with the sentence is determined. In addition, a probability of the sentence being a discourse element is determined by mapping the feature to a model. The model having been generated by a machine learning application based on at least one annotated essay. Furthermore, the essay is annotated based on the probability.

Abstract: Systems and methods for generating trust scores for translations are described herein. According to some embodiments, methods for generating a trust score for a translation may include establishing a trust score for at least a portion of a first translation of a source text translated by a trusted translation system, the trust score representing an accuracy level for the first translation, comparing the first translation of the source text generated by the trusted translation system to a second translation of the source text generated by an untrusted translation system, and determining a trust score for the second translation based upon the comparison.

Abstract: A system, method, and computer program for generating and exploiting an approximate language model are provided. The method comprises generating a language model according to an approximate hashing technique. The language model comprises a plurality of event sequences in a target language, and each member of the plurality of the event sequences is associated with at least one count. The language model is queried for a member of the plurality of event sequences. A probability associated with the member of the plurality of event sequences is determined based on results of the query.

Abstract: Training and translation using trees and/or subtrees as parts of the rules. A target language is word aligned with a source language, and at least one of the languages is parsed into trees. The trees are used for training, by aligning conversion steps, forming a manual set of information representing the conversion steps and then learning rules from that reduced set. The rules include subtrees as parts thereof, and are used for decoding, along with an n-gram language model and a syntax based language mode.

Abstract: A method, system and computer readable medium for hosting a community in multiple languages is disclosed. The method comprises receiving a request from a first member of a community to post content within the community. The content is written in a first language. Next, the content is translated into a second language. Login information is received from a second member. The second member may be associated with a second language. Lastly, the translated content is displayed to the second member. The method may further comprise receiving feedback from the second member relating to the quality of the translation or post edited versions of the automatically produced translation.

Abstract: Systems and methods for creating a mathematical model for use in identifying discourse elements are described. A plurality of first essays relating to a particular subject are received, where each first essay is in an electronic format. Annotations for each first essay are received, where each annotation identifies at least one discourse element. Features are identified with a processor, where each feature is exhibited by at least one identified discourse element. Empirical frequencies are computed with a processor, where each empirical frequency relates to the presence of a feature with respect to the identified discourse elements across the plurality of first essays. Each empirical frequency is associated with the related identified discourse element with a processor. The empirical frequencies are utilized to select discourse elements in at least one second essay.

Abstract: A system and method for aligning words in parallel segments is provided. A first probability distribution of word alignments within a first corpus comprising unaligned word-level parallel segments according to a model estimate is calculated. The model estimate is modified according to the first probability distribution. One or more sub-models associated with the modified model estimate are discriminatively re-ranked according to word-level annotated parallel segments. A second probability distribution of the word alignments within the first corpus is calculated according to the re-ranked sub-models associated with the modified model estimate.