29/06/2022 /Category
As our world grows ever more interconnected, the demand for fast, accurate translation is soaring. The global machine translation market is projected to reach $1.62 billion by 2028, up from $718.9 million in 2021. This growth is made possible by advancements in machine translation technology and it’s fueled by a desire to serve customers better through localization. The best machine translation software on the market today can help you serve more people in more places.
Machine translation (or MT for short) leverages computer programs to translate text from one language to another. The technology has been around since the 1950s, but has become more commercially viable with the rise of machine learning and artificial intelligence.
There are 3 types of machine translation:
Rules-based machine translation (RBMT) came first and relies on bilingual dictionaries and linguistic rules written by humans. It usually translates one word at a time which can result in awkward sentence structures and other inaccuracies. While RBMT can be useful in some instances, it has many disadvantages including the need for extensive human involvement. This type of machine translation has largely been eclipsed by the other two models.
Statistical machine translation (SMT) translates one language into another by first learning from pre-approved example texts. It then applies a statistical model of the associations between words, phrases, and sentences in one language to the second language. SMT outperforms rule-based machine translation, but can still result in unnatural sounding texts and mistranslations.
Neural machine translation (NMT) uses a kind of artificial intelligence called neural networks to translate from one language to another. NMT is able to learn languages and continuously enhance its performance. Once trained, it is faster and more accurate than SMT. Neural MT is quickly becoming the industry standard in the development of machine translation engines.
The best machine translation software can help you quickly and easily translate large volumes of content such as websites, legal contracts, or product documentation. The main advantages of machine translation are:
Speed - machine translation software can translate text almost instantaneously. The same task might take a human translator hours or even days to complete. Being able to get more done in less time makes your business more efficient.
Cost - with efficiency comes cost reductions. Even when you factor in MTPE, machine translation is highly cost effective, especially when you have a lot of content to be translated.
Scale - being able to translate more content in less time for less money allows your organization to scale and serve new markets faster.
Perhaps the most well-known machine translation service, Google Translate uses neural machine translation to translate text in more than 100 different languages. While the basic app is free, the Translation API Advanced option offers additional customization to support industry slang or domain-specific terms.
Powered by Amazon Web Services (AWS), Amazon Tranlate is a neural machine translation engine that supports 75 languages. You can use Amazon Translate to translate unstructured text documents and build applications that work in multiple languages. It’s a pay-as-you-go solution that is both customizable and scalable.
ModernMT offers neural machine translation that is able to learn in real time from your corrections in order to improve its translations. It is also better than some competitors at considering the context of a document. ModernMT is currently trained on 46 languages.
Part of Azure Cognitive Services, Microsoft Translator is another NMT that supports more than 100 languages. Microsoft claims that their system has been able to translate news items from Chinese to English as well as human translators. Conveniently, Microsoft Translator is integrated into other Microsoft services and can be used to translate Word documents, Excel spreadsheets, and PowerPoint slides.
DeepL claims to be the world’s most accurate translator. It uses a technique called deep learning to train its automatic language software to catch subtle nuances which allows for more precise translations. However, DeepL currently only supports 28, primarily European languages.
Founded in 1968, Systran is one of the oldest and most established machine translation providers. It’s also the only one to be open-source, meaning users have more freedom and agility in how they program the software. Systran currently supports 50 languages.
Most famous for winning Jeopardy!, IBM’s artificial intelligence, called Watson, offers a neural machine translation engine that can translate documents from one language to another while preserving formatting. It supports 27 languages and is particularly strong in the financial services, IT, and education sectors.
Developed by one of Europe’s leading tech companies, Yandex Translate supports 98 languages. It uses a hybrid of both neural and statistical machine translation. Documents are sent to both the NMT and SMT engines then an algorithm selects the better result.
Unbabel is an artificial intelligence-powered human translation platform. It uses neural machine translation with crowdsourced human translators to achieve the speed and scale of MT with the authenticity of native speakers across 30 languages.
Omniscien also uses a hybrid of neural and statistical machine translation. They offer different tools that are optimized for specific purposes, such as subtitle translation. Their tools are highly customizable so even the most complex data can achieve high quality in a variety of use-cases. Omniscien currently supports 48 languages.
Which machine translation software is best for you is going to depend on a variety of factors including:
Your industry - some machine translation software is better than others at handling the specific vocabulary of your industry.
Language pairs - the translation engine needs to be trained on the language pair you are working with.
Content type - specialized content such as marketing content, user interfaces, or technical documentation might require specific language software.
Budget - neural machine translation will have a higher price point than statistical machine translation.
If you are unsure, our experts can help you find the best language translation software for your unique needs.