Here at Lilt, we’re passionate about making the content of the world more accessible to all by providing a more efficient and affordable language translation and localization ecosystem. And with work becoming more digital and commerce increasingly headed online, it’s more apparent than ever the need for localized content.
While we continue to grow our network of translators and expand the services and software we offer to customers, we focus just as much internally on building a team of inspiring and motivated people to help tackle that crucial mission. We’ve brought on some of the industry’s most experienced leaders to share their expertise and help further Lilt’s goals.
After close to 30 years in the industry working for the largest companies, I was drawn to Lilt because of the new technology that they had brought into the market and the new process of localization. In the industry, we haven't seen much change over the years. There isn’t much that really integrates together, so it can be very difficult for both customers and service providers to work together.
With Lilt, it was refreshing to see the importance placed on translators, who are of the essence of our business. Without translators, we wouldn't have an industry. Since they’re often freelancers, there's always the possibility that they don’t know when their next job is going to be, so it’s crucial to focus on their success. The combination of that mission, coupled with the amazing technology, was really what made me want to join the Lilt team.
There’s been so much progress in many industries around the world, with new electronics, smartphones, computers - you name it. But in the localization industry, many companies are still relying on a tool that’s 30 years old. I think the biggest change early on was the introduction of translation memories.
Before translation memories, prices were so high that localization was almost cost-prohibitive, so companies only focused on a few languages if they could. But with the advent of translation memories, companies could recycle words so they were able to do more than the traditional four or five languages - they could do eight, maybe even ten or twelve languages.
The next big milestone was machine translation - with mixed results. At first, the quality wasn’t very good with MT. As we moved to statistical MT, there were some improvements in quality for certain types of content. But even so, for high quality content, the quality was not good enough and was only useful for some support sites.
From there, some customers moved to machine translation plus post-editing (MT+PE), and while it was more costly than just MT, it was still a lot cheaper than pure translation. But post-editing created other problems. One was that translators tend to dislike it. They get published content from the MT that they have to fix - not very rewarding for a high caliber, high quality translator that is able to do so much more. And not only that, but the machine keeps giving them the same errors over and over until you retrain the engine, which often didn't happen for a long time. It was not very efficient.
One of the biggest changes, though, has been Neural MT, which has truly been a game changer. Since a neural network is trained on a source text, it doesn’t require the same systems that traditional MT does. Instead, it can learn and understand translation in a way that earlier systems simply can’t. It learns faster, performs better, and is really a dramatic improvement over the earlier statistical MT systems.
Since then, other tools have sprouted up. Translation management systems (TMS) have become popular, and even though they don't particularly add much progress to the actual translation quality, they do help navigate the maze of technology and suppliers that the industry has. Overall, a lot of change has happened, but progress has been stagnant for a while.
That’s why I was excited to join Lilt - the technology and approach to the industry is remarkable. The company focus is different, as it intends to support translators by giving them technology to make them more efficient. Cutting out post-editing and giving translators a tool that learns from their translations makes the process faster and more rewarding.
I think the big change is gonna be the same as it was before. Budgets don't get bigger in translation and localization, especially now with the situation around the world. It's going to be more challenging for translation departments or marketing departments to ask for even more budget to translate. At the same time, communication is key and is becoming more global. Before, you could translate the first five or ten languages and capture a huge user base. Now, you need to do a lot more and dive into the long tail of languages.
So as companies need to do more to reach consumers worldwide, the questions shift focus a bit. How can you translate more languages? How can you translate more content while keeping the same budget or less?
I think the industry is going to have to change the way it works in translation. It’s always been expensive, and companies are going to have to maintain high quality, which comes with human translators. Lilt combines the human translators with the AI/automation, and it's quite unique. And I think more companies will have to look at changing to a localization process that becomes more efficient, becomes less costly, while maintaining the high quality.
It depends on the level of experience for the organization. For a team that is new to localization, it’s not uncommon to think that you press a button and it’s done. But not all starting companies think about their brand as it relates to the locale they’re translating for. So having that awareness upfront isn’t always easy to come by.
Another common pitfall for companies early on is that they forget to lay the foundation for localization. Often, it’s because there’s a focus on the product, and they usually just need a quick translation that needs to be done. When that’s the case, they don’t always think ahead to future expansion, so localization usually takes a back seat. Later on, though, the process isn’t in place so it becomes harder to follow the right steps consistently.
With bigger more experienced companies, though, it’s difficult to uproot a process that you’ve become comfortable with. If you have an older, broken car that you know well, you usually just make little fixes here and there to keep your 30 year old car running. You don’t often think about changing cars until you see the newer, better car with a more efficient engine and better features. For larger companies that have a heavy rooted process in place, it can be easier to continue with that workflow even if it doesn’t work as well as it should.
So that mind shift - having to go to something completely new and different - is a big leap. Change takes courage, so it’s usually easier for the companies that are just starting and haven't translated before. But some companies with long localization experience are doing it already. Some are actually changing the way they do localization and embracing innovation.
Especially these days - you need to be able to do a lot more with a lot less, you need to change the way you do things.
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