Abstract: Documents in source natural languages are translated into target natural languages using a computer-implemented translation that is configured to operate within the domain of the subject matter of the documents that imposes specialized requirements for translation and readability. Subject matter specific documents typically include domain-specific terminology, are subject to various regulatory guidelines, and have different readability requirements depending on the intended reader. The computer-implemented translation applies machine-learning techniques that deconstruct elements of the subject matter specific document into a standard data structure and perform pre-processing steps to tokenize digitized document text to identify the correct sentence structure and syntax for the target natural language to optimize translation by, e.g., a neural machine translation engine.

Abstract: Documents in source natural languages are translated into target natural languages using a computer-implemented translation that is configured to operate within the domain of the subject matter of the documents that imposes specialized requirements for translation and readability. Subject matter specific documents typically include domain-specific terminology, are subject to various regulatory guidelines, and have different readability requirements depending on the intended reader. The computer-implemented translation applies machine-learning techniques that deconstruct elements of the subject matter specific document into a standard data structure and perform pre-processing steps to tokenize digitized document text to identify the correct sentence structure and syntax for the target natural language to optimize translation by, e.g., a neural machine translation engine.

Abstract: A computer-implemented method for performing quality review of life science documents is described. One or more of the life science documents are scanned by a mobile device, wherein the one or more life science documents are sent to a database. Language, image, rotation, and noise are among the content that is checked among the life science documents, and wherein similarities, suspicious changes, document layouts, and missing sections are checked among the one or more life science documents. In addition, feedback is sent by a system to an originator of the life science documents based on the content regarding imaging, rotation, and noise and the similarities, suspicious changes, document layouts and missing sections.

Abstract: Documents in a source natural language are translated into one or more target natural languages using a computer-implemented translation tool that is configured to operate within the domain of life science that imposes specialized requirements for translation and readability. Life science documents typically include domain-specific terminology, are subject to various regulatory guidelines, and have different readability requirements depending on the intended reader. The computer-implemented translation tool applies machine-learning techniques that deconstruct elements of a life science document into a standard data structure and perform pre-processing steps to tokenize digitized document text to identify the correct sentence structure and syntax for the target natural language to optimize translation by a translation engine such as a neural machine translation engine.