Examples of using 神经机器翻译 in Chinese and their translations into English
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他们开发出了名为谷歌神经机器翻译（GNMT）的系统。
这一新功能由神经机器翻译服务AmazonTranslate提供支持。
This new feature is powered by Amazon Translate, a neural machine translation service.NeuralMachineTranslation神经机器翻译.
Vocabulary for neural machine translation.该系统被重写，在一个名为“谷歌神经机器翻译”的新平台上运行，将一切都转移到一个深度学习环境中。
The system was rewritten torun on a new platform called Google Neural Machine Translation, moving everything to a deep learning environment.很多人都不知道的一点是，神经机器翻译其实是在中国首次开创并得到发展的，之后又成为了产品。
What many people might not be aware is that neural machine translation was first pioneered and developed, and shipped as a product in China.Combinations with other parts of speech
此外，谷歌神经机器翻译系统能够不断地学习和改进，因而应用时间越长，它翻译出来的东西会越自然越地道。
Moreover, the Neural Machine Translation system learns over time and improves, resulting in better and more natural 我们提出了一种使用单个神经机器翻译（NMT）模型在多种语言之间进行翻译的简洁优雅的解决方案。
We propose a simple, elegant solution to use a single Neural Machine Translation(NMT) model to translate between multiple languages.但神经机器翻译甚至比之前的模型更依赖于大量的训练数据。
But neural machine translation is even more dependent on huge sets of training data than its predecessor models.他从事过很多有趣的工作，如神经机器翻译、小型无人机的避障，以及给老年人使用的社交机器人。
Interesting things he worked on are neural machine translation, obstacle avoidance on small drones, and a social robot for elderly people.最终，谷歌计划在app中使用神经机器翻译系统来翻译全球103种语言。
Eventually, Google plans to use neural machine translation for all 103 languages in the app.虽然神经机器翻译只是NLG的一个分支，但NMT获得了大量关注，有许多方法专门为该任务开发。
While neural machine translation(NMT) is an instance of NLG, NMT receives so much attention that many methods have been developed specifically for the task.他做过一些有趣的事情，包括神经机器翻译、小型无人机上避障以及面向老年人的社交机器人。
Interesting things he worked on are neural machine translation, obstacle avoidance on small drones, and a social robot for elderly people.至于机器翻译，你知道美国有很多关于神经机器翻译的PR。
I think that 在我看来，2016年的大事件主要集中在深度强化学习、生成模型、神经机器翻译这三个领域。
The main events of 2016 from my point of view have been in the areas of deep reinforcement learning,generative models, and neural machine translation.你可能还记得，9月份Google宣布其神经机器翻译系统已经上线。
You may remember that back in September, Google announced that its Neural Machine Translation system had gone live.实际上，这个故事有着不广为人知的另一面：神经机器翻译是在中国开创、研发和使用的。
In fact one aspect of thisstory that's not widely known: Neural machine translation was a technology first pioneered and developed and shipped in China.幸运的是，对于不想等引擎“长大”的企业来说，还有神经机器翻译。
Fortunately, for businesses that don't want towait for an engine to“grow up,” there's neural machine translation.在WMTA主要的EMNLP会议中，机器翻译会议，特别是神经机器翻译将会很惹眼。
In the main EMNLP conference that follows the WMT, conference sessions on 最近一次转变到神经机器翻译是由深度学习技术驱动的。
The most recent shift towards neural machine translation is powered by deep learning technologies.我们将继续扩展神经机器翻译技术的边界，向每一个使用Facebook的用户提供更高质的翻译。
We will continue to push the boundaries of neural machine translation technology, with the aim 对于实际应用，神经机器翻译的一个考量因素是我们为系统提供一个句子后，它到底需要多长时间进行翻译。
One consideration with neural machine translation for practical applications is how long it takes to get a 本次报告还将总结和探讨神经机器翻译未来发展的机遇和挑战。
The tutorial will also summarize and discuss challenges andopportunities for future developments in neural machine translation.他指出，机器翻译发展到今天已到了第三代即神经机器翻译（.
Nowadays, 在文章的后面，我们将使用这样的动画来描述神经机器翻译模型中的向量。
Later in the post,we will use 考虑到深度神经网络的使用，该领域被称为神经机器翻译。
Given that deep Unbabel创立于2013年，融合了神经机器翻译、自然语言处理（NLP）和质量估算算法技术，可以在70多对语言组合之间进行自动翻译。
Founded in 2013, Unbabel's technology merges neural machine translation, natural language processing(NLP), and quality estimation algorithms to automate 神经机器翻译.
Neural Machine Translation.
