| 摘要 |
A quality-prediction engine predicts a trust level associated with translational accuracy of a machine-generated translation. Training a quality-prediction may include translating a document in a source language to a target language by executing a machine-translation engine stored in memory to obtain a machine-generated translation. The training may further include comparing the machine-generated translation with a human-generated translation of the document. The human-generated translation is in the target language. Additionally, the training may include generating a mapping between features of the machine-generated translation and features of the human-generated translation based on the comparison. The mapping may allow determination of trust levels associated with translational accuracy of future machine-generated translations that lack corresponding human-generated translations. Machine-generated translations may then be credibly provided by translating a document from a source language to a target language by executing a machine-translation engine stored in memory to obtain a machine-generated translation, predicting a trust level of the machine-generated translation by executing a quality-prediction engine stored in memory, and outputting the machine-generated translation and the trust level.
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