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公开(公告)号：US10223356B1
公开(公告)日：2019-03-05
申请号：US15278735
申请日：2016-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Thibault Pierre Seillier , Pallami Bhattacharjee , Paul Christopher Cerda , William Joseph Kaper , Paul Kasper , Kelly Duggar Wiggins
Abstract: A content management system (CMS) and a translation management system (TMS) can utilize content dimensions for content items to manage and translate the content items between languages. Machine and human translations of complex dynamic content can also be improved by pre-rendering the content to remove localization-related syntax prior to machine or human translation. Content items can also be scored as to their suitability for localization prior to translation, and translation can be skipped for content items that do not have a sufficiently high score. Semantic and natural language processing (NLP) techniques can also be utilized for content categorization and routing. Translations of content items can also be continuously refined and higher quality re-translated content can be provided in an automated fashion.
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公开(公告)号：US10275459B1
公开(公告)日：2019-04-30
申请号：US15278840
申请日：2016-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Paul Kasper , Pallami Bhattacharjee , Paul Christopher Cerda , William Joseph Kaper , Thibault Pierre Seillier , Kelly Duggar Wiggins
IPC: G06F17/28
Abstract: A content management system (CMS) and a translation management system (TMS) can utilize content dimensions for content items to manage and translate the content items between languages. Machine and human translations of complex dynamic content can also be improved by pre-rendering the content to remove localization-related syntax prior to machine or human translation. Content items can also be scored as to their suitability for localization prior to translation, and translation can be skipped for content items that do not have a sufficiently high score. Semantic and natural language processing (NLP) techniques can also be utilized for content categorization and routing. Translations of content items can also be continuously refined and higher quality re-translated content can be provided in an automated fashion.
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公开(公告)号：US10229113B1
公开(公告)日：2019-03-12
申请号：US15278788
申请日：2016-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Kelly Duggar Wiggins , Pallami Bhattacharjee , Paul Christopher Cerda , William Joseph Kaper , Paul Kasper , Thibault Pierre Seillier
IPC: G06F17/28
Abstract: A content management system (CMS) and a translation management system (TMS) can utilize content dimensions for content items to manage and translate the content items between languages. Machine and human translations of complex dynamic content can also be improved by pre-rendering the content to remove localization-related syntax prior to machine or human translation. Content items can also be scored as to their suitability for localization prior to translation, and translation can be skipped for content items that do not have a sufficiently high score. Semantic and natural language processing (NLP) techniques can also be utilized for content categorization and routing. Translations of content items can also be continuously refined and higher quality re-translated content can be provided in an automated fashion.
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Patent Agency Ranking
公开(公告)号：US10261995B1
公开(公告)日：2019-04-16
申请号：US15278869
申请日：2016-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Paul Christopher Cerda , Pallami Bhattacharjee , William Joseph Kaper , Paul Kasper , Thibault Pierre Seillier , Kelly Duggar Wiggins
Abstract: A content management system (CMS) and a translation management system (TMS) can utilize content dimensions for content items to manage and translate the content items between languages. Machine and human translations of complex dynamic content can also be improved by pre-rendering the content to remove localization-related syntax prior to machine or human translation. Content items can also be scored as to their suitability for localization prior to translation, and translation can be skipped for content items that do not have a sufficiently high score. Semantic and natural language processing (NLP) techniques can also be utilized for content categorization and routing. Translations of content items can also be continuously refined and higher quality re-translated content can be provided in an automated fashion.
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公开(公告)号：US10185713B1
公开(公告)日：2019-01-22
申请号：US14867932
申请日：2015-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Michael Denkowski , Alon Lavie , Gregory Alan Hanneman , Austin Matthews , Matthew Ryan Fiorillo , Robert Thomas Olszewski , Christopher James Dyer , William Joseph Kaper , Alexandre Alexandrovich Klementiev , Gavin R. Jewell
Abstract: Technologies are disclosed herein for statistical machine translation. In particular, the disclosed technologies include extensions to conventional machine translation pipelines: the use of multiple domain-specific and non-domain-specific dynamic language translation models and language models; cluster-based language models; and large-scale discriminative training. Incremental update technologies are also disclosed for use in updating a machine translation system in four areas: word alignment; translation modeling; language modeling; and parameter estimation. A mechanism is also disclosed for training and utilizing a runtime machine translation quality classifier for estimating the quality of machine translations without the benefit of reference translations. The runtime machine translation quality classifier is generated in a manner to offset imbalances in the number of training instances in various classes, and to assign a greater penalty to the misclassification of lower-quality translations as higher-quality translations than to misclassification of higher-quality translations as lower-quality translations.
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公开(公告)号：US10268684B1
公开(公告)日：2019-04-23
申请号：US14868166
申请日：2015-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Michael Denkowski , Alon Lavie , Gregory Alan Hanneman , Matthew Ryan Fiorillo , Laura Josephine Kieras , Robert Thomas Olszewski , William Joseph Kaper , Alexandre Alexandrovich Klementiev , Gavin Richard Jewell
Abstract: Technologies are disclosed herein for statistical machine translation. In particular, the disclosed technologies include extensions to conventional machine translation pipelines: the use of multiple domain-specific and non-domain-specific dynamic language translation models and language models; cluster-based language models; and large-scale discriminative training. Incremental update technologies are also disclosed for use in updating a machine translation system in four areas: word alignment; translation modeling; language modeling; and parameter estimation. A mechanism is also disclosed for training and utilizing a runtime machine translation quality classifier for estimating the quality of machine translations without the benefit of reference translations. The runtime machine translation quality classifier is generated in a manner to offset imbalances in the number of training instances in various classes, and to assign a greater penalty to the misclassification of lower-quality translations as higher-quality translations than to misclassification of higher-quality translations as lower-quality translations.
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公开(公告)号：US10248396B1
公开(公告)日：2019-04-02
申请号：US15707790
申请日：2017-09-18
Applicant: Amazon Technologies, Inc.
Inventor： Kelly Duggar Wiggins , David Armour , Jeremy Boynes , William Cary Hall , Christopher A. Heilman , Robert E. Hicks , William Joseph Kaper , Addison Page Phillips , Thibault Pierre Seillier
Abstract: A system for conducting a code review of program source code including translation of content in the program source code may include a source control system. The system may also include a resource file translator to facilitate translation of the content from a first language into second languages. Upon receipt of a code review request, the source control system may notify a workflow manager that the resource files contain the content for translation, and the workflow manager may notify a resource file translator that the program source code contains the content for translation. The resource file translator may cause translation of the resource files into translated resource files. The source control system may receive program source code under review from a code reviewer interface, and the resource file translator may update the program source code under review with the translated resource files.
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公开(公告)号：US09959271B1
公开(公告)日：2018-05-01
申请号：US14868083
申请日：2015-09-28
Applicant: Amazon Technologies, Inc.
Inventor： Kartik Goyal , Alon Lavie , Michael Denkowski , Gregory Alan Hanneman , Matthew Ryan Fiorillo , Robert Thomas Olszewski , Ehud Hershkovich , William Joseph Kaper , Alexandre Alexandrovich Klementiev , Gavin R. Jewell
CPC classification number: G06F17/2818 , G06F17/2854
Abstract: Technologies are disclosed herein for statistical machine translation. In particular, the disclosed technologies include extensions to conventional machine translation pipelines: the use of multiple domain-specific and non-domain-specific dynamic language translation models and language models; cluster-based language models; and large-scale discriminative training. Incremental update technologies are also disclosed for use in updating a machine translation system in four areas: word alignment; translation modeling; language modeling; and parameter estimation. A mechanism is also disclosed for training and utilizing a runtime machine translation quality classifier for estimating the quality of machine translations without the benefit of reference translations. The runtime machine translation quality classifier is generated in a manner to offset imbalances in the number of training instances in various classes, and to assign a greater penalty to the misclassification of lower-quality translations as higher-quality translations than to misclassification of higher-quality translations as lower-quality translations.
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