First of all, as Turkey’s manufacturing sector is not as large as, let’s say, Germany’s or Japan’s, texts related to this sector are not translated very frequently. There are multiple reasons for this phenomenon. Translations made from Turkish to other languages are minuscule in comparison. In Turkey, the translation market I work in, translations are usually done from other languages to Turkish. Then we can continue with English to Japanese translation.
First, let’s discuss the job opportunities Japanese to English translators and translation agencies have. Whether you are translating from Japanese to English or from English to Japanese, the Japanese translation market has a lot to offer. Then we will explain how to utilize machine translation tools for translating to and from Japanese and lastly how to better use Google Translate when translating between English and Japanese.
In this blog post, we will dive deeper into the Japanese translation market with job opportunities and average salaries for Japanese translators. They said the Translated Wikipedia Biographies dataset can be used to evaluate gender bias in MT output along common translation errors - among which the researchers singled out three, pro-drop, possessives, and gender agreement.In our first blog post for this series, we have looked into the intricacies of the Japanese language and common issues translators may face in Japanese to English and English to Japanese translation. These often occur when articles refer to a person explicitly in early sentences of a paragraph, but there is no explicit mention of the person in later sentences,” the researchers said in a Jblog post. “Because they are well-written, geographically diverse, contain multiple sentences, and refer to subjects in the third person (and so contain plenty of pronouns), Wikipedia biographies offer a high potential for common translation errors associated with gender. The ultimate goal, according to Google researchers, is to improve machine learning systems focused on gender and pronouns in translation by coming up with a benchmark for accuracy. In its ongoing quest to reduce gender bias in machine translation (MT), Google has released a dataset of Translated Wikipedia Biographies.
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