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Naver Papago (Korean: 네이버 파파고), shortened to Papago and stylized as papago, is a multilingual machine translation cloud service provided by Naver Corporation. The name Papago comes from the Esperanto word for parrot , Esperanto being a constructed language.
Ulukau: The Hawaiian Electronic Library is an online, digital library of Native Hawaiian reference material for cultural and Hawaiian language studies. The services are free and are provided and maintained by Kahaka ‘Ula O Ke’elikolani College of Hawaiian Language at the University of Hawaii at Hilo [1] and Ka Waihona Puke 'Ōiwi Native Hawaiian Library at Alu Like. [2]
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]
Naver Dictionary was launched in 1999, supporting the English language. [3] [4] It began launching mobile applications in 2010. [5] The product Line Dictionary, launched in 2014, was part of the platform. [2] By 2022, the platform reportedly had 60 different sub services, [6] and was the most popular online dictionary service in South Korea by ...
Hawaiian is a predominantly verb–subject–object language. However, word order is flexible, and the emphatic word can be placed first in the sentence. [1]: p28 Hawaiian largely avoids subordinate clauses, [1]: p.27 and often uses a possessive construction instead.
Urimalsaem (Korean: 우리말샘) is an online open source Korean language dictionary. It was launched on October 5, 2016, with an initial set of 1,109,722 headwords. It aims to capture neologisms (new words), jargon, colloquial expressions, and words specific to dialects.
Some prominent Korean-American figures with Korean names include novelist and artist Theresa Hak Kyung Cha, journalist Kyung Lah, "Lost" actor Yunjin Kim, novelist Min Jin Lee, U.S. Representative ...
Google Translate's NMT system uses a large artificial neural network capable of deep learning. [1] [2] [3] By using millions of examples, GNMT improves the quality of translation, [2] using broader context to deduce the most relevant translation. The result is then rearranged and adapted to approach grammatically based human language. [1]