\n\t\t\t\t\t\t\t\t\t\t\t\t\tGergely V\u00e1ndor\n\t\t\t\t\t\t\t\t\t\t\t\t\tProduct Manager at memoQ\n\t\t\t\t\t\t\t<\/footer>\n\t\t\t<\/article>\n\n\t\tWhat Does this Mean for the Translator Community?\n\t<\/h3>\n\t Today machine translation usually involves post-editing work done by humans. This post-editing process ensures the content meets the highest quality level desired by the client. For translators, this means they are mastering a new skill that requires a new type of training \u2014 post-editing work. It can be challenging for translators to adapt to this new job skill, but fortunately, if they do, there are many benefits.<\/p>\n
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Machine translation can help them deliver work faster, and therefore, take on more work. It can also make their jobs easier. The technology gives translators a starting point, an opportunity to improve quality, and the ability to churn out more content quickly.<\/p>\n
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According to Arle Lommel, Senior Analyst at Common Sense Advisory, and Donald A. DePalma, Chief Strategist at Common Sense Advisory, \u201c[Companies now] use the machine to perform the boring work of translating simple content and ensuring terminological consistency, while they route complex and interesting content to humans to take advantage of their skills.\u201d<\/p>\n
\n\t\tPrices Go Down, but Job Opportunities Go up\n\t<\/h3>\n\t When machines do most of the legwork, naturally the prices of translated content go down. This is making many translators across the industry nervous. They\u2019re asking questions like, \u201cWhat\u2019s my new role now that machine translation is readily available?\u201d \u201cWill I still get the same amount of work?\u201d and \u201cHow does this impact my pay?\u201d<\/p>\n
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Fortunately, with post-editing needs, the job opportunities are still there. But, there needs to be an efficient way to measure post-editing efforts and then pay translators accordingly. Fortunately, memoQ, among other similar translation software companies, now offer product features to help measure these efforts accurately, giving translators a unique advantage in a shifting industry.<\/p>\n
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According to V\u00e1ndor, \u201cThere are two approaches: one is to measure the time it takes for a translator to translate the document to its final state. The other approach is measuring the amount of edits that were done.\u201d<\/p>\n
\n\t\tThe Question is \u2014 Will Neural Machine Translation be a Game Changer for Translators?\n\t<\/h3>\n\t Earlier generations of machine translation technology work like a dictionary and use algorithms to decipher grammar, syntax, and phraseology. Therefore, they still require post-editing efforts from humans. However, machine learning (also known as neural MT) \u201clearns\u201d how to translate languages from the information that is given to it. The more content it translates, the \u201csmarter\u201d the technology gets.<\/p>\n
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According to a recent article in Forbes, the role of translators has changed (and will continue to change) with a greater use of neural machine translation. (2) Neural MT reduces the amount of post-translation, post-editing work needed. But, it also gives smaller companies access to translation services, so they can request work when they didn\u2019t have the budget to do so before. This can actually create more jobs for translators.<\/p>\n
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However, Bal\u00e1zs Kis, Co-Founder and Chairman of the Board at memoQ, doesn\u2019t necessarily think neural MT is a true game changer.\u201c It looks like neural MT could be a breakthrough because the translations are well-formed, and for the most part, grammatical. But, this also makes it more difficult to spot missing or altered parts,\u201d says Kis. As a result, translators are needed to ensure the output is high-quality content.<\/p>\n
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It looks like only time will tell how neural MT will impact our industry.<\/p>\n
\n\t\tBut this we Know: MT Technology is Here to Stay\n\t<\/h3>\n\t In recent years, and most likely in 2019, the use of machine translation has grown and will continue to grow exponentially. Until recently, engineers and information technology experts spent a great deal of time setting up an MT system. It required a large investment in resources and server space. But now, cloud-based and hosted solutions make launching machine translation technology simpler, faster, and more affordable. As a result, we believe you will see even more of this technology in 2019.<\/p>\n
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There\u2019s also a trend in integrating machine translation technology with speech recognition devices. Say hello to Alexa, Siri, and other popular products. This technology allows a face-to-face dialogue, despite language differences. For example, in 2019, you might see more machine translation technology integrated with newer speech recognition devices, as well as within older, everyday devices, like photocopiers and megaphones.<\/p>\n
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No one can deny machine translation technology is here to stay \u2014 and it\u2019s quickly evolving in ways we never imagined. From neural machine translation to integrations with speech recognition devices, MT is evolving, and becoming ingrained in our world and how we communicate. But, there are still big questions to answer. We need to embrace the technology, but also spend significant time and resources ensuring it delivers the best quality. And ensuring there\u2019s still a place for human translators.<\/p>\n\t
References:<\/p>\n
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1 \u201cMachine Translation: 2018\u201d Arle Lommel and Donald A. DePalma.<\/p>\n
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2 \u201cWill Machine Learning AI Make Human Translators An Endangered Species?\u201d Bernard Marr.<\/p>\n","protected":false},"excerpt":{"rendered":"
No one can deny machine translation technology is here to stay, but there are still big questions to answer: What\u2019s the role of translators now that machine translation is readily available? Will they still get the same amount of work? How do we measure their efforts?<\/p>\n","protected":false},"author":14,"featured_media":84,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"categories":[6,10],"class_list":["post-48","page","type-page","status-publish","has-post-thumbnail","hentry","category-6","category-trend"],"yoast_head":"\n
Machine Translation Evolves\u2026 But How Does It Impact Translators\u2019 Jobs?<\/title>\n \n \n \n \n \n \n \n \n \n \n \n\t \n\t \n\t \n \n \n \n \n \n\t \n