https://github.com/hingston/japanese

This repo contains a list of the 44,998 most common Japanese words in order of frequency, as determined by the University of Leeds Corpus.
https://github.com/hingston/japanese

japanese japanese-characters japanese-dictionary japanese-language

Last synced: 3 months ago
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This repo contains a list of the 44,998 most common Japanese words in order of frequency, as determined by the University of Leeds Corpus.

• Host: GitHub
• URL: https://github.com/hingston/japanese
• Owner: hingston
• License: other
• Created: 2018-09-13T11:54:08.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2018-09-13T12:44:30.000Z (over 6 years ago)
• Last Synced: 2025-01-06T15:49:25.702Z (5 months ago)
• Topics: japanese, japanese-characters, japanese-dictionary, japanese-language
• Homepage: http://corpus.leeds.ac.uk/frqc/internet-jp.num
• Size: 269 KB
• Stars: 67
• Watchers: 3
• Forks: 11
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

        
About This Repo

===============

This repo contains a list of the most common Japanese words in order of frequency, as determined by the [University of Leeds Corpus](http://corpus.leeds.ac.uk/frqc/internet-jp.num).

Usage

-----

This repo is useful as a corpus for typing training programs. According to analysis of the [Oxford English Corpus](https://en.oxforddictionaries.com/explore/what-can-corpus-tell-us-about-language/), the 7,000 most common English lemmas account for approximately 90% of usage, so a 15,000 word training corpus is more than sufficient for practical training applications.

To use this list as a training corpus in [Amphetype](https://code.google.com/archive/p/amphetype/), paste the contents into the "Lesson Generator" tab with the following settings:

    Make **3** copies of the list

    Divide into sublists of size **3**

    Add to sources as **15000-japanese-words**

In the "Sources" tab, you should see **15000-japanese-words** available for training. Set WPM at 10 more than your current average, set accuracy to 98%, and you're set to train.

Enjoy!