{"id":246434,"date":"2023-06-30T09:39:05","date_gmt":"2023-06-30T13:39:05","guid":{"rendered":"https:\/\/www.motionpoint.com\/?post_type=blog&p=246434"},"modified":"2023-07-28T14:17:24","modified_gmt":"2023-07-28T18:17:24","slug":"debunking-myths-of-automated-translation-separating-fact-from-fiction","status":"publish","type":"blog","link":"https:\/\/www.motionpoint.com\/blog\/debunking-myths-of-automated-translation-separating-fact-from-fiction\/","title":{"rendered":"Debunking Myths of Automated Translation: Separating Fact from Fiction"},"template":"","blog_categories":[107,15],"resource_categories":[37,24,32,31,25,18],"targeted_localized_audience":[],"document_categories":[152,146,170,157,171],"class_list":["post-246434","blog","type-blog","status-publish","hentry","blog_categories-translation-technology","blog_categories-website-translation","resource_categories-content-type-blog-post","resource_categories-role-business-strategist","resource_categories-business-goal-optimize-performance","resource_categories-business-goal-streamline-operations","resource_categories-role-technologists-developers","resource_categories-topic-website-translation","document_categories-beyond-website-translation","document_categories-blog-post","document_categories-business-leader","document_categories-machine-translation","document_categories-marketer"],"acf":{"article_word_count":"2471","article_read_time":"10","blog_short_description":"As the world is moving towards AI and automation in the translation industry, what are the biggest misconceptions about it? We're here to set the record straight and help you choose the right translation solution for your business. ","news_inline_styles":"","blog_video_id":"","article_body":"

In the age of technological advancements, automated translation has gained significant attention. However, they have also been surrounded by myths and misconceptions. From speculation about translation output quality to the elimination of human review, find out some of the most common myths about machine <\/span>website translation tools<\/a>.<\/span>\u00a0<\/span><\/p>\n

What is Automated Translation?<\/span><\/b>\u00a0<\/span><\/h2>\n

Automated translation is when translation workflows happen without any human intervention. Some examples of automated translation are proxy solutions and the translation mechanism used to translate, for example, machine translation, human translation, AI, MTPE (machine translation post-edit) and more. Automated translation systems are designed to mimic the human translation process by utilizing algorithms and statistical models trained on large amounts of bilingual or multilingual data. These models learn patterns and statistical relationships between words, phrases, and sentences in different languages. Based on these patterns, the system generates translations by selecting the most probable target language equivalents for the given input.<\/span>\u00a0<\/span><\/p>\n

There are different approaches to automated translation, including rule-based, statistical, and <\/span>neural machine translation (NMT)<\/span><\/a>. Rule-based machine translation relies on predefined linguistic rules and dictionaries, while statistical machine translation utilizes statistical models that analyze patterns in large corpora of bilingual text. Neural machine translation, the most recent approach, uses artificial neural networks to learn patterns and relationships in parallel bilingual or multilingual data.<\/span>\u00a0<\/span><\/p>\n

Myth 1: Automated Translation Alone Achieves Human-Level Accuracy\u00a0<\/span>\u00a0<\/span><\/h2>\n

In a survey conducted by CSA Research in 2020, 58% of respondents said that they use machine translation to translate content, while 35% said they use human translation. The remaining 7% use a combination of both. Automated translation systems have made remarkable progress, but they are still far from achieving human-level accuracy. Research conducted by industry experts reveals that the average quality of machine translation is around 65 to 85 out of 100, depending on the language pair and domain.<\/span>\u00a0<\/span><\/p>\n

So how can you better your machine translation? Since it depends heavily on how it\u2019s trained, you need to make sure you\u2019re using the right tools. Using Neural Machine Translation (NMT), specifically a brand adapted model, makes the process easier and will help produce better results over time.\u00a0<\/span>\u00a0<\/span><\/p>\n

Training a neural machine translation (NMT) system for a specific domain involves several steps to ensure the best possible results. Here’s a recommended approach for training a brand domain NMT:<\/span>\u00a0<\/span><\/p>\n