- Every day, Facebook performs some 4.5 billion automatic translations — and as of yesterday, they’re all processed using neural networks.
- While the phrase-based system translated sentences word by word, or by looking at short phrases, the neural networks consider whole sentences at a time.
- “With the new system, we saw an average relative increase of 11 percent in BLEU — a widely used metric for judging the accuracy of machine translation — across all languages compared with the phrase-based systems,” the company said.
- When a word in a sentence doesn’t have a direct corresponding translation in a target language, the neural system will generate a placeholder for the unknown word.
- “Neural networks open up many future development paths related to adding further context, such as a photo accompanying the text of a post, to create better translations,” the company said.
Every day, Facebook performs some 4.5 billion automatic translations — and as of yesterday, they’re all processed using neural networks. Previously, the social networking site used simpler…
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