3 Ways the Translator’s Role Has Evolved with AI

翻译角色随着人工智能演变的三种方式

2020-12-30 14:00 unbabel

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AI and machine translation have come a long way since its early days. Even so, human translators are still a very critical part of the process. Many companies rely on hybrid human-machine translation to complete critical tasks in areas such as multilingual customer service, where high stakes interactions can make or break customer satisfaction and long-term loyalty. Human translators are essential to ensuring that these conversations are accurate and reflect the local, cultural nuances of each language. With the evolution of machine translation, the role of the translator itself has changed significantly. Let’s take a look at how. 1. Unlocking more opportunity Let me start by saying that there are still many types of translators out there. Some professional translation jobs, such as those at literary publishing houses, haven’t changed much with the advent of machine translation. There’s too much nuance, for example, in a poetry book or a young adult fiction novel for a machine to effectively understand it. However, there are many new jobs for freelance translators that can be picked up from anywhere in the world, at any time. For example, many Unbabel editors in our community pick up customer service translation jobs on the side or in their spare time to earn extra income. Our community members range from recent graduates to caregivers that want to have the flexibility to work outside the traditional “work hours.” Some editors who have faced financial hardships due to the pandemic have been able to make extra income. These new opportunities fill the freelancer availability gap, and are made possible by AI-powered platforms like Unbabel. What’s more, freelancers now have access to qualified roles such as annotation and term base creation. These talented translators can now learn and evolve into roles that once were restricted to academic or research groups. And, as we’ll cover next, human feedback from a new role of post-editor helps improve AI’s algorithms. 2. Translators play a key role in machine translation quality Just like humans, machines are all about learning and continuous improvement. However, machine translation algorithms could not improve without human feedback. With Unbabel editors, translation corrections happen in very practical ways, but add up to major contributions for the entire machine learning community. In general, a new role of post-editor has evolved to meet the demands of machine translation. Say, for example, an editor is working on corrections for an agent’s gaming company. The editor may correct a phrase in the translation that isn’t accurate in Brazilian Portuguese. These fixes will be sent directly to the gaming company’s customer, so the responses are as personal and accurate as possible. In the meantime, the machine translation team receives these fixes, which are applied to the algorithm so it can “learn” from its mistakes. Unbabel editors are also asked to participate in machine translation research projects. Their corrections on words and phrases generated by the algorithm are used to improve machine learning research, and the results are shared with the community – in many cases through open source projects. Editors are interested and invested in what Unbabel is doing, because they know exactly how their fixes are helping both customers and the research community at large. 3. Global translators have found new communities This year, office workers globally have learned what it’s like to work remotely. It can feel isolating, even for those who are used to working from home. That’s why communities and collaboration are so important. AI has opened up new online communities for translators that can create unexpected connections. For example, the Unbabel community helps translators learn from one another, laugh at machines’ mistakes, and share their experiences. Translators in the community also get feedback from customers, so they can celebrate their successes. Best of all, they can both help each other do their jobs and build new friendships, just as colleagues in an office might do. The human and AI relationship In the coming years, the relationship between translators and machines is sure to evolve even further. Unbabel is proud to be at the forefront of this movement, opening up new opportunities for freelance translators and sharing our work with the machine translation research community. To learn more about how our unique blend of human and machine translation provides always-on, multilingual customer support, check out our case studies.
自早期以来,人工智能和机器翻译已经取得了长足的进步。即便如此,人工译员仍然是整个过程中非常关键的一部分。许多公司依靠人机混合翻译来完成多语言客户服务等领域的关键任务,其中高风险的互动可能会影响客户满意度和长期忠诚度。人工翻译至关重要,可以确保这些对话的准确性,反映每种语言本土文化中的细微差别。 随着机器翻译的发展,译者本身的角色发生了显著变化。让我们来看看是如何变化的。 1.给出更多机会 首先,我要说的是,现在的翻译人员还是有很多类型的。一些类似于文学出版社的专业翻译工作,并没有因为机器翻译的出现而有什么变化。比如说,一本诗集或一本青年小说中的细微差别太多,机器无法有效理解。 然而,对于自由译者来说,可以随时随地接取很多新的工作。例如,我们社区许多Unbabel平台上的编辑在业余时间从事客户服务翻译工作,以赚取额外收入。我们的社区成员包含了从刚毕业的学生到希望在传统 "工作时间 "之外有弹性工作的医护人员。一些因大流行病而面临经济困难的编辑,已经能够靠此赚取额外的收入。这些新的机会填补了自由职业者的可用性缺口,Unbabel等人工智能驱动的平台使得这些机会成为可能。 更重要的是,自由职业者现在有机会担任合格的角色,如注释和术语库创建。这些有才华的翻译人员现在可以学习和发展到曾经仅限于学术或研究团体的角色。而且,正如我们接下来要介绍的那样,来自后期编辑这个新角色的人类反馈有助于改进AI的算法。 2.译者对机器翻译质量至关重要 就像人类一样,机器也是要学习和不断改进的。然而,如果没有人类的反馈,机器翻译算法就无法改进。有了Unbabel编辑平台,修正翻译的方式更加实用,加起来对整个机器学习社区有重大贡献。总的来说,为了满足机器翻译的需求,后期编辑这个新角色应运而生。 比如说,一位编辑正在为一家代理游戏公司进行翻译修正。编辑可能会在翻译中纠正一个巴西葡萄牙语不准确的短语。这些修正将直接发送给该游戏公司的客户,因此尽可能的给予个性且准确的回复。同时,机器翻译团队会收到这些修正,并将其应用到算法中,以便它能从错误中 "学习"。 Unbabel的编辑也参与到机器翻译研究项目中来。他们将修正算法生成的单词和短语用于改进机器学习研究,并在大多数情况下通过开源项目将结果与社区共享。编辑们对Unbabel的工作很感兴趣,也很投入,因为他们清楚地知道这项修正工作是如何帮助客户和整个研究团体的。 3.全球翻译人员找到了新的社区 今年,全球的上班族都了解了远程工作的感受。即使对于那些习惯于在家工作的人来说,也会感到孤立无援。这就是为什么社区和协作如此重要。AI为翻译人员开辟了新的在线社区,可以创造意想不到的联系。 例如,Unbabel社区帮助翻译人员相互学习,调侃机器犯的错误,并分享他们的经验。社区中的译员还能得到客户的反馈,因此他们可以庆祝自己的成功。最重要的是,他们就像办公室里的同事一样,既可以通过互相帮助完成工作,又可以建立新的友谊。 人与人工智能的关系 在未来的几年里,译员和机器之间的关系肯定会进一步发展。Unbabel 翻译平台很荣幸能站在这一运动的前沿,为自由译员开辟新的道路,并与机器翻译研究界分享我们的工作。要了解更多关于独特的人机翻译融合如何提供随时在线的多语言客户支持,请查看我们的案例研究。

以上中文文本为机器翻译,存在不同程度偏差和错误,请理解并参考英文原文阅读。

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