Universal translation
First Claim
1. A method for identifying a most likely source language of a snippet, comprising:
- receiving an indication of the snippet, wherein the snippet is a digital representation of words or character groups;
determining two or more possible source languages for the snippet;
generating, by one or more machine translation engines, two or more translations of the snippet each having a specified translation source language,wherein at least one of the two or more translations of the snippet is generated having a first of the two or more possible source languages for the snippet set as the specified translation source language, andwherein at least another of the two or more translations of the snippet is generated having a second of the two or more possible source languages for the snippet other than the first of the two or more possible source languages for the snippet set as the specified translation source language;
computing, by one or more translation score models trained using or more neural networks, accuracy scores for at least two of the generated two or more translations of the snippet;
producing a confidence factor for each of at least two selected possible source languages for the snippet, wherein the confidence factor for each selected possible source language is produced based on one or more of the computed accuracy scores that has a source language corresponding to the selected possible source language; and
selecting, as the most likely source language, the possible source language for the snippet that is associated with a highest confidence factor.
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Accused Products
Abstract
A likely source language of a media item can be identified by attempting an initial language identification of the media item based on intrinsic or extrinsic factors, such as words in the media item and languages known by the media item author. This initial identification can generate a list of most likely source languages with corresponding likelihood factors. Translations can then be performed presuming each of the most likely source languages. The translations can be performed for multiple output languages. Each resulting translation can receive a corresponding score based on a number of factors. The scores can be combined where they have a common source language. These combined scores can be used to weight the previously identified likelihood factors for the source languages of the media item.
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Citations
20 Claims
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1. A method for identifying a most likely source language of a snippet, comprising:
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receiving an indication of the snippet, wherein the snippet is a digital representation of words or character groups; determining two or more possible source languages for the snippet; generating, by one or more machine translation engines, two or more translations of the snippet each having a specified translation source language, wherein at least one of the two or more translations of the snippet is generated having a first of the two or more possible source languages for the snippet set as the specified translation source language, and wherein at least another of the two or more translations of the snippet is generated having a second of the two or more possible source languages for the snippet other than the first of the two or more possible source languages for the snippet set as the specified translation source language; computing, by one or more translation score models trained using or more neural networks, accuracy scores for at least two of the generated two or more translations of the snippet; producing a confidence factor for each of at least two selected possible source languages for the snippet, wherein the confidence factor for each selected possible source language is produced based on one or more of the computed accuracy scores that has a source language corresponding to the selected possible source language; and selecting, as the most likely source language, the possible source language for the snippet that is associated with a highest confidence factor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A non-transitory computer-readable storage medium storing instructions that, when executed by a computing system, cause the computing system to perform operations for identifying confidence factors for snippet source languages, the operations comprising:
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receiving an indication of a snippet, wherein the snippet is a digital representation of words or character groups; receiving an indication of a viewer of the snippet; determining an output language associated with the viewer of the snippet; generating, by one or more machine translation engines, two or more translations of the snippet of the two or more translations each having a specified translation source language and each of the two or more translations being in an output language matching the output language associated with the viewer of the snippet, wherein at least one of the two or more translations of the snippet is generated having a first of two or more possible source languages for the snippet set as the specified translation source language, and wherein at least another of the two or more translations of the snippet is generated having a second of the two or more possible source languages for the snippet other than the first the two or more possible source languages for the snippet set as the specified translation source language; computing, by one or more translation score models trained using or more neural networks, accuracy scores for at least two of the generated two or more translations of the snippet; and producing a confidence factor for each of at least two selected possible source languages for the snippet, wherein the confidence factor for each selected possible source language is produced based on one or more of the computed accuracy scores that has a source language corresponding to the selected possible source language. - View Dependent Claims (15, 16, 17, 18)
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19. A system for generating a translation of a snippet, comprising:
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a memory; one or more processors; an interface configured to receive an indication of the snippet, wherein the snippet is a digital representation of words or character groups; a pre-translation language identifier configured to determine two or more possible source languages for the snippet; a machine translation engine configured to generate two or more translations of the snippet, each of the two or more translations of the snippet having a specified translation source language, wherein at least one of the two or more translations of the snippet is generated having a first of the two or more possible source languages for the snippet set as the specified translation source language, and wherein at least another of the two or more translations of the snippet is generated having a second of the two or more possible source languages for the snippet other than the first the two or more possible source languages for the snippet as the specified translation source language; a translation scoring model trained using one or more neural networks and configured to compute accuracy scores for at least two of the generated two or more translations of the snippet; and a confidence score generator configured to produce a confidence factor for each of at least two selected possible source languages for the snippet, wherein the confidence factor for each selected possible source language is produced based on one or more of the computed accuracy scores that has a source language corresponding to the selected possible source language; wherein the interface is further configured to provide from the generated two or more translations of the snippet, as translations of the snippet, translations where the specified translation source language is the possible source language with the highest confidence factor. - View Dependent Claims (20)
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Specification