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: A method for machine translation, comprising receiving a source string in a source language, an indication of a target language, and user identification information. The method includes using the user identification information to identify at least one memory with user-specific translation data. The method includes tokenizing the source string, using at least one processor, to produce a tokenized source string comprising any unique temporary textual elements associated with corresponding target textual elements during tokenization. The method includes obtaining a translated string from a translator, the translated string being at least a partial translation of the tokenized source string and including all of the unique temporary textual elements. The method includes generating an output string using at least one processor, the generation comprising replacing all of the unique temporary textual elements in the translated string with the associated target textual elements.

Abstract: A platform and related components are provided for managing and executing various processes involving distributed, crowd and automated resources, including human and machine language-based translation, are described, including methods and systems for creating and intelligently distributing cognizable translation units among internal workers, outsourcing centers, and crowd workers and methods and systems for on-demand translation.

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 and methods for multi-engine machine translations are disclosed. Exemplary methods and systems involve normalizing and/or tokenizing a source string using user-specific translation data. The user-specific translation data may include glossary data, translation memory data, and rule data for use in customizing translations and sequestering sensitive data during the translation process. The disclosed methods and systems also involve using one or more machine translation engines to obtain a translation of the normalized and/or tokenized source string.

Abstract: The present application is directed towards methods and systems for providing anonymous and traceable external access to internal linguistic assets. The methods and systems described allow users the freedom to use a linguistic resource with the security that their identities and interactions with the resource are shielded from other users. Simultaneously, the system maintains a mechanism to trace all user's interactions with a resource to ensure the integrity of the asset is not jeopardized and to easily identify a problem with a user's access without broadcasting their identity or actions.

Abstract: Systems and methods for multi-engine machine translations are disclosed. Exemplary methods and systems involve normalizing and/or tokenizing a source string using user-specific translation data. The user-specific translation data may include glossary data, translation memory data, and rule data for use in customizing translations and sequestering sensitive data during the translation process. The disclosed methods and systems also involve using one or more machine translation engines to obtain a translation of the normalized and/or tokenized source string.

Abstract: A method for local, computer-aided translation using remotely-generated translation predictions includes the step of determining that a translation stored in a remote translation memory is useful in translating a first portion of a local document. A local machine receives the translation. Prior to receiving a request form a translator for the translation, a determination is made that the remote translation memory stores an updated version of the translation. The updated version of the translation is identified as useful in translating a second portion of the document. The local machine generates a translation of the second portion of the document through reuse of the updated version of the translation, responsive to the identification of the utility of the updated version of the translation in translating the second portion of the document.

Abstract: A method for local, computer-aided translation using remotely-generated translation predictions includes the step of determining that a translation stored in a remote translation memory is useful in translating a first portion of a local document. A local machine receives the translation of the first portion of the document. The local machine stores, in a local cache, an alternate version of the translation created by a translator. The alternate version of the translation is identified as useful in translating a second portion of the document. The local machine generates a translation of the second portion of the document through reuse of the alternate version of the translation of the first portion of the document, responsive to the received identification of the utility of the alternate version of the translation of the first portion of the document to the second portion of the document.

Abstract: A method for local, computer-aided translation using remotely-generated translation predictions includes the step of determining that a translation stored in a remote translation memory is useful in translating a first portion of a local document. A local machine receives the translation of the first portion of the document. The local machine stores, in a local cache, an alternate version of the translation created by a translator. The alternate version of the translation is identified as useful in translating a second portion of the document. The local machine generates a translation of the second portion of the document through reuse of the alternate version of the translation of the first portion of the document, responsive to the received identification of the utility of the alternate version of the translation of the first portion of the document to the second portion of the document.

Abstract: A method for local, computer-aided translation using remotely-generated translation predictions includes the step of receiving, by a remote translation memory, at least one portion of a document in a source language for translation into a target language. The remote translation memory determines, prior to receiving a request from a translator for a translation of a second portion of the document, that a translation of the at least one portion is useful in translating the second portion, or in translating a portion of a second document. A local machine receives the translation of the first portion and an identification of the utility of the translation. A translation agent on the local machine generates a translation through reuse of the translation of the first portion of the document, responsive to the received identification of the utility of the translation of the first portion of the document.

Abstract: A method for local, computer-aided translation using remotely-generated translation predictions includes the step of determining that a translation stored in a remote translation memory is useful in translating a first portion of a local document. A local machine receives the translation of the first portion of the document. The local machine stores, in a local cache, an alternate version of the translation created by a translator. The alternate version of the translation is identified as useful in translating a second portion of the document. The local machine generates a translation of the second portion of the document through reuse of the alternate version of the translation of the first portion of the document, responsive to the received identification of the utility of the alternate version of the translation of the first portion of the document to the second portion of the document.

Abstract: A method for local, computer-aided translation using remotely-generated translation predictions includes the step of receiving, by a remote translation memory, at least one portion of a document in a source language for translation into a target language. The remote translation memory determines, prior to receiving a request from a translator for a translation of a second portion of the document, that a translation of the at least one portion is useful in translating the second portion, or in translating a portion of a second document. A local machine receives the translation of the first portion and an identification of the utility of the translation. A translation agent on the local machine generates a translation through reuse of the translation of the first portion of the document, responsive to the received identification of the utility of the translation of the first portion of the document.

Abstract: A method for local, computer-aided translation using remotely-generated translation predictions includes the step of determining that a translation stored in a remote translation memory is useful in translating a first portion of a local document. A local machine receives the translation. Prior to receiving a request form a translator for the translation, a determination is made that the remote translation memory stores an updated version of the translation. The updated version of the translation is identified as useful in translating a second portion of the document. The local machine generates a translation of the second portion of the document through reuse of the updated version of the translation, responsive to the identification of the utility of the updated version of the translation in translating the second portion of the document.

Abstract: A computer-implemented system, method, and product are provided to propagate an externally produced translation of a first occurrence of a word, phrase, or other group of characters to be translated (referred to herein as a “translatable source segment”) in a first source file to at least one occurrence of a corresponding target segment in one or more target files of a target project. The corresponding target segment corresponds with a second occurrence of the translatable source segment in any of the one or more source files. The source files may have the same file format, or two or more of the source files may have different file formats. Also, two or more source files may have character formats that are different from each other, and/or they may be written in different languages. In one implementation, the propagator propagates the externally produced translation to all corresponding target segments in the target project that correspond with the translatable source segment.

Abstract: A computer-implemented system, method, and product associate words, phrases, or other characters (“words”) to be translated with previous translations of such words, if a previous translation exists. The words to be translated, and their identifying attributes (such as, for example, formatting information), are extracted from one or more source files. The previous translations, and their identifying attributes, are extracted from one or more target files. If a previous translation does not exist, the words to be translated, and their attributes, are copied to create a pseudo-previous translation, with attributes. Each word to be translated is associated with a corresponding previous translation based upon commonalities of their attributes. Such words may also be associated based upon their respective locations in their respective files. Each word to be translated, and its attributes, may be stored with a previous translation in a source-target pair record of a source-target pair database.