Right Tools + Right Time = Right Workflow

Combining Context Aware translation with “hyper-localization” to transform content localization

Creating hyper-localized, translated content that is ready for distribution to any region worldwide is easy with AI-powered machine translation. Simply select your source language and target language pairs and run your translation job through your service provider’s translation engine. It’s that easy, right?  Guess again.

The Complexity of Translating Hyper-Localized Content

In theory, translating hyper-localized content is easy in terms of process and steps. In reality, successfully translating hyper-localized content is a highly complex process that requires the right combination of tools, workflow, and personnel to execute well.

Professional translators are now required to consider multiple dialects, formalities, and slang within a country or region to appeal to and be better understood by a wider audience. Translators must also craft the translations within the technical requirements established by their customers, such as maximum characters per line, lines per segment, and mergeable gap; minimum and maximum caption duration; and timing styles. These expectations require that translators have the right balance of precision and creativity, while maintaining the right level of nuance to best convey the intended meaning of the content’s creator.

It’s important to have the right expectations when considering hyper-localization, understanding that translations become more subjective and less literal due to the creative measures taken to meet the multi-dialect and technical requirements.

The Role of Workflow in Hyper-Localization

In spite of the technological advances in AI-powered machine learning, the day-to-day workflow remains a key factor in evolving the localization process to a “hyper” level.

Given the insatiable demand for localized content on streaming platforms and linear/broadcast networks, Localization Service Providers (LSPs) need streamlined workflows that unlock the full power of AI to support efficient and cost-effective localization. There are simply not enough linguists to translate all this content, especially when content is translated from more source languages and translated into more languages than ever before.

Hyper-localization - It’s not just for content

Hyper-localization extends well beyond the sole domain of content translation and is considered the new superpower in marketing. Everyone has been influenced by hyper-localized marketing in some shape or form. Analytics and demographical information obtained from web traffic help marketers personalize their offerings to appeal to local consumers. The following are a few examples of hyper-localized promotions: a national chain retailer running promotions with local sports teams to appeal to a regional fanbase, mom-and-pop stores cross-promoting with local colleges to offer discounts, and retail websites geo-targeting specific cities and regions to personalize promotional offers.

There are clear benefits to the right hyper-localization approach. According to the 2021 State of Personalization Survey conducted by research firm Segment, more than half (60%) of consumers say they would likely become repeat buyers after a personalized shopping experience with a retailer (up from 44% in 2017). These year-end findings also coincide with the world’s emergence from the COVID pandemic, a time when nearly everyone globally was forced into a hyper-local mindset due to lockdowns. It’s no surprise that these habits are likely to remain for the long term.

Challenges in Hyper-Localized Content Translation

It's no different in content translation. Why would a viewer in the southern part of Germany appreciate receiving content tailored to a northern dialect?

Pulling off a hyper-localized approach successfully is a challenge and requires technical tools to analyze data and track changes in customer preferences. We must also recognize the evolving changes in languages and the complex nuances often found within the same language that can make accurate translations a logistical nightmare. Varying sentence structure rules, idiomatic expressions, compound words, multi-word verbs, and sarcasm are only a few examples of these complex nuances within the same language.

Opportunities and Growth in the Localization Industry

Recognition of these opportunities has led to the machine translation market becoming extremely competitive. Currently, there are more than 50 machine translation vendors, but XL8 is the only media-focused MT company. We firmly believe that machine translation will permanently change the landscape of the global localization industry.

The media space is such a highly segmented and specialized sector that requires a level of accuracy; creativity; storytelling capabilities; a deep understanding of cultural nuance, formality, and genre; and language fluency – all while complying with each content owner or distributor’s unique technical specifications and profiles. To support these needs, specialized data and engine training pipelines are required for developing machine translation engines that meet these requirements.

Introducing XL8's MediaCAT Platform

To respond to the industry’s immediate need for efficiency and cost savings, XL8 launched its AI-powered MediaCAT platform in September 2022 to create a seamless, web-based platform with asset management, in-line editing, and automation capabilities that complement XL8’s machine translation services. XL8’s full array of media content services includes text and subtitle translations; auto subtitling based on speech recognition (ASR), auto-captioning, and synchronization; and synthesized dubbing and voice-overs.

There’s still more work to be done

For all our advancements in technology, there are still many challenges impacting the localization industry – both from a technical and business perspective.

With the growing demand for subtitled hyper-localized content, one of the biggest challenges that can’t be immediately solved is the talent gap. This challenge is pervasive across all industries that require localized messaging. It will take time to build up our human resources. AI-powered machine translation technology is the only effective option to help companies scale to handle unlimited market demand and work at the speed of their business.

Focusing linguists’ valuable creative and technical skills on refinement tasks through Machine Translation Post Editing (MTPE) enables repetitive and tedious tasks to be done through automation and machine translation. Not only does this allow linguists to focus on what they do best, but it also provides more time devoted to translation accuracy while increasing the throughput of each linguist.

The importance of Collaboration: linguists and right tools

Localization professions in Media & Entertainment are introducing AI-powered machine translation into their workflow; however, some professionals are still apprehensive and have many questions. Will the migration to machine translation result in lost jobs? How do I choose the right machine translation engines for my business? Will I still gain efficiency even when post-editing is required? How can I integrate machine translation when I’m so busy that I don’t have the mental bandwidth to learn something new?

To answer these questions, it’s critical that we work collaboratively to address these concerns. The quick answer is no - AI-powered machine translation is not a job-killer. XL8 views MT as a job-saver because it helps LSPs become more profitable and increase their throughput with their existing staff. Whether you are an LSP, a large production facility, or a distribution company, it’s important to explore how we can rethink our workflows together.

While it takes head space and a commitment to implement new technology, the benefit is the immediate cost savings and efficiencies gained during a recession where we’re required to do more with less. Having a relationship with a partner who can provide training and collaborate on the best ways to integrate machine translation will go a long way to successful user adoption and outcome.

Written by Tim Jung, CEO and founder of XL8

This content was written by Tim Jung in the Feb 2023 Issue of the “Multilingual Magazine,” published by Multilingual Media.

Based on this article, Tim, CEO of XL8, and Josh, CRO of XL8, had an interview with Nimdzi Insights back in May. In this video, Hyper-localization is an increasingly important part of the globalization and localization industries. They explored important considerations that LSPs must make when working with dialectal and cultural variances within the same country. Check out the full video here.

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