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点击,翻译-杭州网站建设为你呈现

时间:2023-01-08     作者:杭州网站建设【转载】   来自:微信派

(点击右上 ···,选择“全文翻译”,查看文章)

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Once again, the WeChat translation team won three trophies.


They won four trophies last year and a championship in 2020.


The WeChat translation is the winner of WMT2022(Conference on Machine Translation). This competition is recognized as the top international machine translation competition in the global academic community. The competition is held once a year, and is known as the "hundred flowers" or "Oscar" of machine translation.


Every year, the WeChat translation team tries something different. In the past two years, five categories including the English-Chinese translation, the Chinese-English translation, the Japanese-English translation, the English-Japanese translation and the English-German translation in the news field won the title. This year, the WeChat translation entered the new track : won the English-German and German-English translation champions in the dialogue translation competition; and the English-Chinese Translation Champion in the biomedical field translation competition.


Why does WeChat translation win frequently?


In this regard, the WeChat translation team announced the secret of the championship for the first time.


They said it wasn't difficult, it was actually very simple.


The WeChat translation team adopted the Mix-AAN Transformers architecture with excellent performance and diversity. When entering the new translation track and facing the challenges of many strong competitors, they first did this when training data:


  • Data enhancement

In simple terms, it is to increase the amount and the diversity of data that can be used for training.


  • Training optimization

In simple terms, it is to provide a variety of complex training environments to improve the anti-noise ability of the translation model.


  • Model integration

Self-BLEU is used to measure the diversity of models, and the search algorithm is continuously improved. In WMT 2022, the team continues to adopt this algorithm.

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