Machine Translation Method and Apparatus, and Storage Medium

A machine translation system, comprising:

• a first machine translation apparatus, comprising:
• a first memory storing first instructions;
• and
• a first processor configured to execute the first instructions, which cause the first processor to be configured to:
• obtain a source document that is to-be-translated, wherein the source document comprises a character of a source language;
• convert the source document into a first target document comprising a character of a first target language, wherein the source language is different from the first target language;
• a second machine translation apparatus, comprising:
• a second memory storing second instructions;
• and
• a second processor configured to execute the second instructions, which cause the second processor to be configured to:
• obtain the source document;
• convert the source document into a second target document comprising a character of a second target language, wherein the second target language is different from the first target language and the source language;
• a recommendation apparatus, comprising:
• a third memory storing third instructions;
• and
• a third processor configured to execute the third instructions, which cause the third processor to be configured to:
• determine a feature value of each preset feature of each of the first target document and the second target document used to evaluate at least one of a fluency or a fidelity of the first target document and the second target document;
• determine a recommendation rating of each of the first target document and the second target document based on the feature value of each preset feature of each of the first target document and the second target document;
• and
• output a target document with a highest recommendation rating based on the recommendation rating of each of the first target document and the second target document.

A machine translation system, comprising

• a plurality of machine translation apparatuses, wherein each of the machine translation apparatuses comprise:
• a first memory storing first instructions;
• and
• a first processor configured to execute the first instructions, which cause the first processor to be configured to:
• obtain a source document that is to-be-translated, wherein the source document comprises a character of a source language;
• convert the source document into a target document comprising a character of a target language, wherein the source language is different from the target language, wherein each of the machine translation apparatuses converts the source document into a different target document;
• a recommendation apparatus, comprising:
• a second memory storing second instructions;
• and
• a second processor configured to execute the second instructions, which cause the second processor to be configured to:
• determine a feature value of each preset feature of each of the target documents used to evaluate at least one of a fluency or a fidelity of the target documents;
• determine a recommendation rating of each of the target documents based on the feature value of each preset feature of each of the target documents;
• and
• output one of the target documents with a highest recommendation rating based on the recommendation rating of each of the target documents.

A computer program product comprising computer-executable instructions for storage on a non-transitory computer-readable medium that, when executed by a processor, cause an apparatus to be configured to:

• obtain a source document that is to-be-translated, wherein the source document comprises a character of a source language;
• convert the source document into a target document comprising a character of a target language, wherein the source language is different from the target language;
• determine a feature value of each preset feature of each of the target documents used to evaluate at least one of a fluency or a fidelity of the target documents;
• determine a recommendation rating of each of the target documents based on the feature value of each preset feature of each of the target documents;
• and
• output one of the target documents with a highest recommendation rating based on the recommendation rating of each of the target documents.