We usually say China has eight major dialects. Some people also classify Chinese dialects as nine major dialects and ten major dialects. In fact, what we call "eight dialects", "nine dialects", or even "ten great dialects" are only the Han dialects in China. If the language of ethnic minorities is added, Chinese dialects can also be drawn more and more finely.
1. Northern dialect
It is customarily called "official words". There are Northeastern Mandarin, northwest Mandarin, Jin dialect, and southwest mandarin. Taking Beijing dialect as the representative, including the Yangtze River north, Zhenjiang above Jiujiang along the Yangtze River, Sichuan, Yunnan, Guizhou and Hubei, Hunan two provinces in the northwestern part of the Guangxi area, the population accounts for more than 70% of the total number of Han nationality. Living in the area where the Shiren dialect, their natural language belongs to the northern dialect. And from this dialect area to Hong Kong, Macao and Taiwan Ho's people and overseas Chinese, overseas Chinese, Chinese, whose "mother tongue" belongs to the northern dialect.
2. Cantonese dialect
Represented by Guangzhou dialect, it is distributed in most areas of Guangdong province and in southeastern Guangxi. Most of the overseas Chinese in Hong Kong, Australia and the Nanyang and some other countries say Cantonese dialect, which accounts for about 5% of the total population of the Han nationality.
3. Hunan dialect
As the representative of Changsha dialect, it is distributed in most parts of Hunan Province, and the population is about 5% of the total number of Han people. Living in this area where Shiren dialect belongs to Xiang dialect, their language. From this dialect area to Hong Kong, Macao and Taiwan, Ho's ethnic people and overseas Chinese and Chinese, whose "mother tongue" is the Xiang dialect.
4. Gan Fangyan
Represented by Nanchang dialect, it is mainly distributed in Jiangxi province (the eastern part along the river and south part) and Southeast Hubei province. The population accounts for about 2.4% of the total number of Han nationality. This dialect region where Shiren language belongs to Gan dialect. From this dialect area, the people of Ho's and the overseas Chinese and Chinese who live in Hong Kong, Macao and Taiwan are the dialect of the Gan dialect of the "native" angelica.
5. Hakka Dialect
Represented by Meixian dialect in Guangdong, it is mainly distributed in the eastern, southern and northern parts of Guangdong, Southeast of Guangxi, Fujian Province, Jiangxi, and Hunan and Sichuan. The population accounts for about 4% of the total number of Han people. This dialect region where Shiren language belongs to the Hakka dialect. From the dialect area to the HOS and the overseas Chinese and the Chinese who live in Hong Kong, Macao and Taiwan, the "mother tongue" is the Hakka dialect.
6. Fujian Dialect
Represented by Fuzhou dialect, a part of the distribution in the northern part of Fujian province and Taiwan Province, overseas Chinese also have some people say in dialect. The population accounts for about 1.2% of the total number of Han people. This dialect region where Shiren language belongs to the Northern Fujian dialect. What's people from this dialect area moved to Hong Kong and Macao and overseas Chinese, overseas Chinese in Ho, the "mother tongue" as Fujian dialect.
7. Minnan Dialect
Represented by Xiamen dialect, it is distributed in the southern part of Fujian Province, part of Eastern Guangdong province and Hainan Province, and most of Taiwan province. Overseas Chinese there are a lot of people say Minnan dialect, using population accounted for about 3%. The total number of Han dialects where Shiren language belongs to the Minnan dialect. From this dialect area, the people of Ho's and the overseas Chinese and Chinese who live in Hong Kong, Macao and Taiwan, whose "mother tongue" is the dialect of Minnan.
8. Wu dialect
The Wu dialect is known as "Wu Nong fine language" and is represented by the Shanghai dialect. (one is represented by Suzhou dialect). It includes most of Zhejiang Province, including the south of the Yangtze River in Jiangsu province and the east part of Zhenjiang (not in Zhenjiang). The population accounts for about 8.4% of the total number of Han people. Living in the area where the Shiren dialect, Wu dialect belongs to their natural language. And from this dialect area to the Hongkong, Macao and Taiwan Ho's people and the overseas Chinese and Chinese who live abroad, the "mother tongue" belongs to the Wu dialect.
As for the newly discovered "dialect dialect", it is mostly distributed in the area of Guangxi, which is characterized by the erosion of the northern dialect to the southern dialect area.
Here is a special talk on the dialect of Hainan.
Hainan has been a "immigrant area" from ancient times to the present, so the language on the island is also deeply branded as "immigrant". It can be said that the language of Hainan Island is the epitome of the eight major dialects of China. Now, Hainan Island for the Han people of several generations, in addition to pass the "Mandarin", also pass a dozen dialects (including minority languages), such as: Hainan dialect (Minnan dialect), Jun dialect (Southwest Mandarin - northern dialect), "Ai" (Hakka dialect and vernacular Chinese) (Yue Fangyan). In addition, Hainan and Han residents: Danzhou (suspected Guangdong dialect), Mai dialect (suspected Guangdong dialect variation) and words (Lingao suspected Guangxi Zhuang Cun (variation), word language unknown) etc..
Translation quality of course matters.
If you ask just about anyone—even someone with no linguistic training—what makes a translation good, most people will tell you that it has to be accurate. But what does accurate mean? Accuracy, on the other hand, has to do with the similarity of meaning. Surprisingly, while most people can identify that accuracy is important in translation, very few understand what it is. That’s because accuracy gets easily confused with literalness, even though they mean different things. Literalness has to do with the degree of similarity between linguistic forms (e.g. words and grammar).
The conceptual approach to the translation phenomenon is viewed as a deep integration of national cultures, and their interactions. Literary translation should be considered in the context of literary interaction as a part of multi-ethnic factor. Translation Studies in Kazakhstan has had many directions and common issues of prose, poetry and drama, the specifics of the translation process, and the place of translation studies in multicultural literary process has become the subject of translation studies. Automatic translators like Google Translate are great for quick, one-off translation in casual conversation. But Google Translate not only sometimes chooses the wrong translation of the several possible for a word, but it's not very good at putting the words together. In other words, it's prone to botching the grammar in a sentence. Literary translation schools reflect the evolution of transferability categories and contain modern concept of communicative equivalence of the original and the translated texts as a norm of translation accuracy. Modern communicative approach to translation is due to the facts of cross-language communication and translation dominants. Expansion of the original and the translated text communicative equivalence should be tolerant to the type of the receiving audience. The problem of interlinear translation was the object of translators’ attention for a long time.
Something always gets lost in translation. That’s what IKEA found out when a Reddit user slipped its “Gosa Raps” pillow into Google Translate and got back “Cuddle Rapes.” Now that Google Translate works in 50 languages offline for Android phones (which makes it sound like a great travel app), it seemed like a perfect time to test what works, and what doesn’t. Spoiler alert: Proper nouns, beware. And f you think common colloquialisms won’t pop up when you’re traveling or need a translation, think about how often you’re looking for a “cool” restaurant – how likely are you phrase this as a “popular with fashionable people” restaurant? We’re willing to bet not all that often. We decided to send the following snippet from the New York Times to a group of translators working in French, Spanish, and Mandarin. The bit is a challenge to Google Translate because of the various forms of verbs, proper nouns, and language that’s idiomatically American. Machine translation, sometimes referred to by the abbreviation MT (not to be confused with computer-aided translation, machine-aided human translation (MAHT) or interactive translation) is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another.
Here’s a humorous example that illustrates the difference quite well. Years ago I invited some Tanzanian friends over for dinner. I put the food out and said, “We’re going to eat ‘Canadian-style,’ so come to the table and just help yourselves.” However, my Tanzanian guests broke out into an awkward mix of laughter and horror. That’s because “help yourself” translated literally into Swahili has the same meaning as “relieve yourself” in English! So, yes, my translation was literal. But accurate? No way! A much better translation would have been for me to tell my guests, “serve yourselves.” All of this was stated in Swahili, but unfortunately, as a novice speaker, I translated it literally (i.e. word-for-word). When we talk about accuracy in translating God’s Word, we’re talking about meaning and the rule is: nothing should be added, deleted or changed. But it can be difficult to see how this gets applied if you’re only looking at the words. A good translation will, on the surface, look very different from its source text. That’s because meaning emerges out of a larger context than just single words or phrases. The translator must consider that readers bring a whole set of assumptions to the text. Now you may see no problem with what I said.
On a basic level, MT performs simple substitution of words in one language for words in another, but that alone usually cannot produce a good translation of a text because recognition of whole phrases and their closest counterparts in the target language is needed. Current machine translation software often allows for customization by domain or profession (such as weather reports), improving output by limiting the scope of allowable substitutions. This technique is particularly effective in domains where formal or formulaic language is used. It follows that machine translation of government and legal documents more readily produces usable output than conversation or less standardised text. Solving this problem with corpus statistical, and neural techniques is a rapidly growing field that is leading to better translations, handling differences in linguistic typology, translation of idioms, and the isolation of anomalies.
