Insights from the Localization Trenches: A Recap

本地化战壕的启示:综述

2020-07-21 01:40 Lilt

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Building a successful services model is not something that comes by chance. Often, it takes years of experience of trial and error to understand the nuances and specifics requirements that come with delivering a result that wows. We recently hosted a webinar with Samantha Reiss, Lilt’s Head of Services, where she shared her learnings from her experience in the trenches of localization. She’s worked to build localization programs for countless customers over her over 15 years of experience, and she’s taken lessons from each stop in her career. Building a Localization Program When embarking on the journey to create a scalable, world-class localization program, Samantha points to a handful of crucial questions that every organization needs to ask itself. While they may seem obvious, they can cause issues down the road if not addressed up front. Since the goal of the program is to deliver content from start to finish, it’s important to know: What is the work? Who is going to do it? How will they do the work? How long will it take? How much will it cost?  How will we know it’s right? Ultimately, the localization industry is based on transforming content so people around the world can read, understand, digest, and utilize it in their local target language. But before the content can make its way onto the screens and pages of its intended audience, proper goals need to be set to simply understand how to get the content translated. However, Samantha shares a warning: don’t over complicate your process. Follow the 80/20 Rule - roughly 80% of your architecture should fall into a repeatable, predictable process that is known to work, while the remaining 20% can adapt and change to suit the specifics of your project. This not only saves time, it also reduces headaches when problem solving down the line.  Tackling the Misconceptions  In her years of experience, she’s also encountered a number of misconceptions about workflows, processes, results, and more.  For example, one of the common misconceptions she’s run into is the idea that the delivered translated content is accurate, even though a company’s in-country project manager needs to rework the translation upon receipt. How can that be? In her specific instance, it came down to a lack of context.  “Using numbers is great - it allows us to show trends and compare one day to another. But what we also need is feedback and collaboration,” Samantha says. “Having the ability to take the feedback and come out with constructive action planning to improve is really what we want to harness.” Metrics on their own require context - without that context, a 99% accurate translation may mean something very different to the project manager than it does to the translator. Getting input and insight, even from those that may not be directly involved with the localization process, can help shine new light on potential problems and make the team rethink how they define success.  Another common misconception that Samantha has run into in her career is that the translation quality is bad and that it sounds like a machine. This is often the source of angst for everyone involved - translators, language service providers, and customers alike.  However, because Lilt uses a human-in-the-loop approach to adaptive machine translation, the translator involved is able to provide immediate feedback that the system can learn from to prevent this problem. It helps to avoid the more literal and robotic output from raw machine translation and, in many cases, workflows where post-editing is involved.  To learn more about building a scalable localization program that can adapt to your company’s needs, watch Insights from the Localization Trenches with Samantha Reiss on-demand.
一个成功的服务模式的建立并不是偶然的。 通常,需要多年的试错经验才能理解令人惊叹的结果所带来的细微差别和具体要求。 我们最近与Lilt的服务主管Samantha Reiss举行了一次网络研讨会,她分享了她在本地化领域的经验。 她在过去15年的工作经验中为无数的客户建立了本地化项目,并且从职业生涯中的每一站中都吸取了教训。 构建本地化程序 在着手创建一个可扩展的、世界级的本地化项目时,Samantha指出了每个组织都需要问自己的几个关键问题。虽然它们看起来很明显,但如果不提前解决,它们可能会在未来引发问题。由于该计划的目标是从头到尾提供内容,因此必须了解: 这项工作是什么? 谁来做这项工作? 他们将如何做这项工作? 这项工作需要花费长时间? 这项工作需要花费多少钱? 我们怎么知道这项工作正确的? 最终,本地化行业的基础是转换内容,这样全世界的人都可以阅读、理解、消化和使用本地目标语言。但是,在内容进入目标受众的屏幕和页面之前,需要设定适当的目标,以便简单地理解如何将内容翻译出来。 遵循80/20规则-大约80%的体系结构应该属于一个已知有效的可重复、可预测的过程,而剩下的20%可以根据项目的具体情况进行调整和更改。这不仅节省了时间,还减少了解决问题时的头疼问题。 消除误解 在她多年的工作经验中,她也遇到了许多关于工作流程、流程、结果等的误解。 例如,她遇到的一个常见的误解,是认为所交付的翻译内容是准确的,即使一家公司的国内项目经理需要在收到译文后重新进行翻译。怎么可能呢?在她具体的例子中,这归结于缺乏对上下文的理解。 “使用数字是很好的,它使我们能够显示趋势,并将一天与另一天进行比较。但我们也需要反馈和合作,”萨曼莎说。“有能力接受反馈,并提出建设性的行动计划来改进,这才是我们真正想要利用的。” 质量评估本身需要上下文-不考虑上下文,99%准确的翻译对于项目经理和译者来说可能有着非常不同的意义。即使是从那些不直接参与本地化过程的人那里获得信息和见解,也有助于揭示潜在问题,并使团队重新思考如何定义成功。 萨曼莎在职业生涯中遇到的另一个常见误解是,翻译质量差,听起来像机器翻译的一样。 这常常是所有相关人员的焦虑的根源--比如说译者,语言服务提供者和客户。 然而,由于Lilt使用了人与回路的方法来进行自适应机器翻译,因此有关的翻译人员能够提供即时反馈,从而使系统防止这种问题的出现。这种方法有助于避免原始机器翻译的文字化和机械化,在多种情况下,避免涉及到后期编辑的工作流程。 要了解更多有关如何构建一个可变通的本地化程序,来适应您公司的需求,请通过Samantha Reiss on-demand观看本地化战壕中的策略。

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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