Hakka Chinese and Katakana

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Hakka Chinese and Katakana

Hakka Chinese vs. Katakana

Hakka, also rendered Kejia, is one of the major groups of varieties of Chinese, spoken natively by the Hakka people throughout southern China, Taiwan, Hong Kong and throughout the diaspora areas of East Asia, Southeast Asia, and in overseas Chinese communities around the world. is a Japanese syllabary, one component of the Japanese writing system along with hiragana, kanji, and in some cases the Latin script (known as rōmaji).

Similarities between Hakka Chinese and Katakana

Hakka Chinese and Katakana have 4 things in common (in Unionpedia): Cantonese, Chinese characters, Phoneme, Taiwan.

Cantonese

The Cantonese language is a variety of Chinese spoken in the city of Guangzhou (historically known as Canton) and its surrounding area in southeastern China.

Cantonese and Hakka Chinese · Cantonese and Katakana · See more »

Chinese characters

Chinese characters are logograms primarily used in the writing of Chinese and Japanese.

Chinese characters and Hakka Chinese · Chinese characters and Katakana · See more »

Phoneme

A phoneme is one of the units of sound (or gesture in the case of sign languages, see chereme) that distinguish one word from another in a particular language.

Hakka Chinese and Phoneme · Katakana and Phoneme · See more »

Taiwan

Taiwan, officially the Republic of China (ROC), is a state in East Asia.

Hakka Chinese and Taiwan · Katakana and Taiwan · See more »

The list above answers the following questions

What Hakka Chinese and Katakana have in common
What are the similarities between Hakka Chinese and Katakana

Hakka Chinese and Katakana Comparison

Hakka Chinese has 78 relations, while Katakana has 171. As they have in common 4, the Jaccard index is 1.61% = 4 / (78 + 171).

References

This article shows the relationship between Hakka Chinese and Katakana. To access each article from which the information was extracted, please visit:

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