Are you looking to expand your business and reach new global audiences? Well, in today's world, content localization is the key to making that happen. And when it comes to translating your content, machine translation can be a real lifesaver. But, before you jump in, there are a few things you need to know to make sure that you're getting the most out of this powerful tool. In this article, we're going to give you the lowdown on the dos and don'ts of machine translation in content localization.
We'll share some tips to help you get high-quality translations that respect cultural sensitivities, build trust with your target audience, and get your message across effectively. From selecting the right tools to pre-and post-editing, we've got you covered.
So, if you're ready to learn how to use MT to take your business to the next level, then let's dive in!
Machine translation is a cool technology that can help efficiently translate text from one language to another. MT has been around since the mid-20th century. The first system was developed in the 1950s and used rules-based methods to translate text. In the 1980s, statistical methods were introduced, allowing for more accurate translations. In the 2000s, neural machine translation (NMT) emerged, which uses deep learning algorithms to improve translation quality. Since its inception, NMT has achieved significant progress in addressing the previous limitations of older MT systems. 2020 suggested that neural machine translation had an estimated accuracy of 60%-90%. Today, MT is a rapidly evolving field, with continued advancements in AI leading to more accurate translations. With MT, you can grow your business globally without busting the bank.
But, as with all technologies, MT isn’t perfect. It can struggle with understanding context and cultural references in the source language.
So, if you're serious about producing high-quality content that resonates with your target audience, it's essential to use machine translation in conjunction with human translation and editing. This way, you can ensure that your translations are accurate, culturally sensitive, and appropriate for your audience.
When it comes to using MT effectively in content localization, there are some important do's and don'ts to keep in mind. Here are some tips and best practices to help you get the most out of machine translation while avoiding common pitfalls:
By following these do's and don'ts and using MT in conjunction with human expertise, you can achieve high-quality and culturally sensitive translations that resonate with your target audience.
According to Google, Frazier is the world’s number one audio description software. Frazier presents a cost and time-saving solution as an alternative to the laborious and expensive traditional processes of audio description creation. On its website, it claims to deliver audio description scripts up to 10x faster. This is because of its available AI technology that takes care of voice recording, mixing, and mastering.
VIDEO TO VOICE is expanding its reach beyond audio description to upgrade connections for digital media. This includes the integration of Frazier's neural machine translation service. While MT services were previously mocked for producing inaccurate translations, recent upgrades in technology, such as neural networks, have noticeably improved the quality of MT services.
Frazier Video to Voice is a popular choice for clients who need to produce videos in multiple languages. Swiss companies, for example, frequently provide content in the four national languages. Frazier makes it easy to create translations in seconds. After the translation is complete, a second user can perform any necessary post-editing on the translated text. Synthetic voices are used to read the translated audio in a natural-sounding way. Then, the new audio combines with the original soundtrack to create a high-quality, professional broadcast-ready video.
Thanks to the use of neural machine translation, MT is now reliable and affordable for localizing content quickly. With video demand growing rapidly, tools like Frazier are vital for language service providers to keep up with demand and increase their output. By making video content accessible to audiences around the world, Frazier Video to Voice is helping to break down language barriers and bring people closer together.
This is one of the most widely used MT tools. It uses neural machine translation technology to provide translations in over 100 languages. Google Translate is available for free online and as a mobile app. One advantage of Google Translate is that it allows users to input text, documents, and even entire websites for translation. However, the accuracy of translations can vary depending on the complexity of the text and the languages involved.
This is another popular machine translation tool that uses neural MT technology. It supports translation in over 60 languages and can be accessed online or through a mobile app. One unique feature of Microsoft Translator is the ability to translate conversations in real-time. Thus, making it useful for business meetings and international conferences. Additionally, Microsoft Translator offers customization options for companies and organizations that need specific terminology and language models.
This German tool uses artificial intelligence and neural networks to provide accurate translations. It supports translations in 26 languages. It is available for free online or as a paid subscription for more advanced features. One advantage of DeepL is its ability to handle complex sentence structures and idiomatic expressions. These can often be challenging for other machine translation tools. However, DeepL may not be as popular as its counterparts.
Looking to the future, machine translation is likely to continue to improve as technology advances. The rise of artificial intelligence and machine learning will enable more sophisticated and accurate translation systems. These in turn can handle more complex language structures and nuances. However, it's important to remember that machine translation is not a replacement for human translators and editors. Especially, as cultural sensitivity and localization require human judgment and expertise.