谷歌大神給你神翻譯整句處理更通順

網路巨擘谷歌（Google）現在敢對你打包票了，拜技術進步之賜，很多人常用的谷歌翻譯現在已可整句處理譯出語，翻出比以往更加通順的譯文。

聽來簡單，但這可是歷經多年努力，耗費偌大工程才做到的。先前谷歌的技術都只能片段分析語詞，再硬生生地拼湊整合，譯文往往生硬難懂，但既然谷歌的機器現在已能整句翻譯，譯文讀起來理應更貼近母語人士水準。

美聯社與美國著名科技新聞網站CNET報導，這種「神經機器翻譯」（neural machine translation）技術，和谷歌過去幾年間用於辨識照片中人體和物體的技術類似，谷歌形容為10年來翻譯服務的最大進步。

弗雷斯特研究公司（Forrester Research）分析師嘉提葉里（Mike Gualtieri）也認為谷歌的新方法是重大突破，但他預期技術推出初期仍可能犯些尷尬的錯誤，就像照片辨識服務推出之初，會認錯一些東西那樣。

今天開始，谷歌「神經機器翻譯」技術可用於9種語言翻譯，除了英文，法文、德文、西班牙文、葡萄牙文、中文、日文、韓文、土耳其文也能使用。

Google Translate now converts Chinese into English with neural machine translation

Google today is announcing that web and mobile versions of Google Translate are now using a new neural machine translation system for all translations from Chinese into English — and the app conducts those translations about 18 million times a day. Google is also publishing an academic paper on the method.

Previously Google has said that it uses neural networks in Google Translate, but specifically for its real-time visual translation feature. And earlier this yearGoogle senior fellow Jeff Dean told VentureBeat that Google was working on incorporating deep learning into more of Google Translate. Sure enough, today’s contributions are the result of that work, a spokesperson told VentureBeat in an email.

Google has been incorporating deep neural networks into more and more of its applications, including Google Allo and Inbox by Gmail. It’s also helping Google more efficiently run its data centers.

For Google neural machine translation (GNMT), the company is relying on eight-layer long short-term memory recurrent neural networks (LSTM-RNNs), “with residual connections between layers to encourage gradient flow,” the Google researchers wrote in the paper. Once the neural networks have been sufficiently trained with the help of graphics processing units (GPUs), Google relies on its recently unveiled tensor processing units (TPUs) to make inferences about new data.

Neural machine translation has not always been optimal, but Google’s implementation has shown advantages in certain situations.