{"id":9268,"date":"2021-08-25T17:11:04","date_gmt":"2021-08-26T00:11:04","guid":{"rendered":"https://www.microsoft.com\/en-us\/translator/blog\/?p=9268"},"modified":"2021-08-30T11:26:05","modified_gmt":"2021-08-30T18:26:05","slug":"microsoft-translator-releases-literary-chinese-translation","status":"publish","type":"post","link":"https://www.microsoft.com\/en-us\/translator/blog\/2021\/08\/25\/microsoft-translator-releases-literary-chinese-translation\/","title":{"rendered":"Microsoft Translator releases literary Chinese translation"},"content":{"rendered":"

When reading <\/span>ancient\u00a0<\/span>Chinese\u00a0<\/span>poetry, we often marvel at the very wonderful words ancient writers could use to describe people, events, objects, and scenes. This is a splendid cultural treasure that has been left behind for us. However,\u00a0similar to\u00a0Shakespeare<\/span>\u2019<\/span>s\u00a0verses in the English language, the literary Chinese used by these poets is often difficult for modern day people to understand, and the meanings and subtleties embedded within it are frequently lost.\u00a0<\/span>\u00a0<\/span><\/p>\n

To solve this problem, researchers at Microsoft Research Asia adopted the latest neural machine translation techniques to train direct translation models between literary Chinese and modern Chinese, which also results in creating translation capabilities between literary Chinese and more than 90\u00a0other languages<\/a> and dialects in Microsoft Translator. Currently, literary Chinese translation has been integrated into the Microsoft Translator app<\/a>, Azure Cognitive Services Translator<\/a>, and a number of Microsoft products that are supported by Microsoft Translator services.<\/span>\u00a0<\/span><\/p>\n

\"\"<\/span><\/p>\n

Image: The painting from “West Mountain in Misty Rain” by Shen Zhou, Ming Dynasty. The ancient Chinese poem on the painting is from <\/span><\/i>Yong<\/span><\/i>\u00a0<\/span><\/i>Liu, Northern Song Dynasty. The poem depicts the spring scenery in southern China during the Qingming Festival and the prosperity of social life.<\/span><\/i><\/p>\n

Enabling more people to appreciate the charm of traditional Chinese culture<\/span><\/b>\u00a0<\/span><\/p>\n

Literary Chinese\u00a0is an important carrier of traditional Chinese culture. Voluminous books and texts from the\u00a0ancient times\u00a0have\u00a0recorded\u00a0China<\/span>\u2019<\/span>s\u00a0rich and profound culture\u00a0over the past five thousand years. The thoughts and wisdom\u00a0accumulated and\u00a0contained\u00a0in\u00a0them are worthy of continuous exploration and\u00a0thinking.\u00a0<\/span>\u00a0<\/span><\/p>\n

With the help of machine translation, tourists can\u00a0now understand ancient Chinese texts and poems written on historic\u00a0buildings\u00a0and monuments, students now have an extra tool to help them learn Chinese, and researchers\u00a0who are engaged in collating and translating\u00a0ancient\u00a0texts can\u00a0be more productive.\u00a0\u00a0\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

Dongdong Zhang, a\u00a0principal\u00a0researcher at Microsoft Research Asia,\u00a0said,\u00a0\u201cFrom a technical perspective,\u00a0literary Chinese\u00a0can be regarded as a separate language.\u00a0Once translation between\u00a0literary Chinese\u00a0and modern Chinese is realized,\u00a0the\u00a0translation between\u00a0literary Chinese\u00a0and other languages such as English, French, and German becomes a matter of course.\u201d\u00a0<\/span>\u00a0<\/span><\/p>\n

Biggest difficulty of\u00a0literary Chinese\u00a0translation AI model:\u00a0Little\u00a0training data<\/span><\/b>\u00a0<\/span><\/p>\n

The most critical element of AI model training is data. Only when data volume is large enough and its quality high enough <\/span>can\u00a0<\/span>you<\/span> train a more accurate model. In machine translation,\u00a0the training of the model requires bilingual data:\u00a0original text data and target language data.\u00a0The translation of\u00a0literary Chinese\u00a0is very special<\/span>,<\/span> as it’<\/span>s not a language\u00a0used in daily life.\u00a0\u00a0Therefore,\u00a0compared with the translation of other languages, the training\u00a0data\u00a0of\u00a0literary Chinese\u00a0translation is very small, which is not conducive to the training of machine translation models.\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

Although Microsoft Research Asia researchers collected a lot of publicly available\u00a0literary\u00a0and modern Chinese data in the early stages, the original data cannot be directly used.\u00a0Data\u00a0cleaning\u00a0needs to be conducted to\u00a0normalize\u00a0data from different sources,\u00a0various\u00a0formats, as well as\u00a0full-width\/<\/span>half-width\u00a0punctuations<\/span>,<\/span>\u00a0as a means\u00a0to\u00a0minimize the interference of invalid data on model training.\u00a0In this way, the actual available high-quality data is further reduced.\u00a0<\/span>\u00a0<\/span><\/p>\n

According to\u00a0Shuming\u00a0Ma, a researcher at Microsoft Research Asia, in order to\u00a0reduce the data sparseness issue,\u00a0researchers have conducted a great amount of data synthesis and\u00a0augmentation\u00a0work, including:<\/span>\u00a0<\/span><\/p>\n

First,\u00a0common character<\/span><\/b>–<\/span><\/b>\u00a0<\/span><\/b>based\u00a0alignment and expansion\u00a0to increase\u00a0training\u00a0data\u00a0size.\u00a0<\/span><\/b>Different from<\/span>\u00a0<\/span><\/b>translations between Chinese and other languages such as English, French, Russian, etc., literary Chinese and modern Chinese use the same character set. Taking advantage of this feature, researchers at Microsoft Research Asia have used innovative algorithms to allow machine translation to recall common characters, conduct natural alignment, and then further expand to words, phrases, and short sentences, thereby synthesizing a large amount of usable data. <\/span>\u00a0<\/span><\/p>\n

Second, deform sentence structure to improve the robustness of machine translation.\u00a0<\/span><\/b>Regarding<\/span>\u00a0<\/span><\/b>breaks in texts and poems, researchers have added\u00a0a\u00a0number of\u00a0variants to make\u00a0machines\u00a0more comprehensive in learning ancient poems.\u00a0For people, even when they see a sentence\u00a0that is\u00a0structured abnormally, such as a poem segmented into lines based on rhythm rather than full sentences,\u00a0they can still put the parts together and understand it. But\u00a0for a translation model that has never seen such segmentation before, it will likely be confused. Therefore, transformation of data format can not only expand the amount of training data, but also improve the robustness of the\u00a0translation model\u00a0training.\u00a0<\/span>\u00a0<\/span><\/p>\n

Third,\u00a0conduct traditional and simplified character translation training to increase model adaptability.<\/span><\/b> In Chinese, traditional characters exist in both literary and modern Chinese. When researchers trained the model, in order to improve the adaptability of the model, they not only leveraged data in simplified Chinese, but also added data in traditional Chinese, as well as data mixed with traditional and simplified characters. Thus, the model can understand both the traditional and simplified contents, which leads to more accurate translation results.\u00a0 <\/span>\u00a0<\/span><\/p>\n

Fourth, increase the training of foreign-language words to improve the accuracy of translation. <\/span><\/b>When translating modern Chinese into literary Chinese, there are often modern words derived from foreign-language words and new words that have never appeared in ancient Chinese, such as \u201cMicrosoft\u201d, \u201ccomputer\u201d, \u201chigh-speed rail\u201d, and many others like it. To deal with this issue, researchers trained a small model to recognize entities. The model first translated the meaning of the word outside the entity, then filled the entity back in to ensure the accuracy of the machine<\/span>\u2019<\/span>s processing of the foreign words.\u00a0\u00a0\u00a0<\/span>\u00a0<\/span><\/p>\n

\"\"<\/span><\/p>\n

Image: T<\/span><\/span><\/span><\/span>he\u00a0<\/span><\/span><\/span>literary Chinese\u00a0<\/span><\/span><\/span><\/span>translation process<\/span><\/span><\/span><\/em><\/p>\n

In\u00a0addition,\u00a0for informal writing styles such as blogs, forums, Weibo, and so on,\u00a0the machine translation model has been trained specifically\u00a0to\u00a0further\u00a0improve\u00a0the robustness of translation between modern and\u00a0literary\u00a0Chinese.\u00a0<\/span>\u00a0<\/span><\/p>\n

Dongdong Zhang expressed, \u201cBased on the current translation system, we will continue to\u00a0enrich\u00a0the data set and improve the model training method to make it more robust and versatile. In the future,\u00a0the method may not only be used for\u00a0literary Chinese\u00a0translation, but\u00a0can also be extended to other application\u00a0scenarios.\u201d<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

When reading ancient\u00a0Chinese\u00a0poetry, we often marvel at the very wonderful words ancient writers could use to describe people, events, objects, and scenes. This is a splendid cultural treasure that has been left behind for us. However,\u00a0similar to\u00a0Shakespeare\u2019s\u00a0verses in the English language, the literary Chinese used by these poets is often difficult for modern day people to understand, and the meanings….<\/span><\/p>\n

CONTINUE READING \"Microsoft Translator releases literary Chinese translation\"<\/span><\/a><\/p>","protected":false},"author":54,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[13,5,69,73,6,74],"tags":[],"acf":[],"yoast_head":"Microsoft Translator releases literary Chinese translation - Microsoft Translator Blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https://www.microsoft.com\/en-us\/translator/blog\/2021\/08\/25\/microsoft-translator-releases-literary-chinese-translation\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Microsoft Translator releases literary Chinese translation - Microsoft Translator Blog\" \/>\n<meta property=\"og:description\" content=\"When reading ancient\u00a0Chinese\u00a0poetry, we often marvel at the very wonderful words ancient writers could use to describe people, events, objects, and scenes. 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