jreadability 1.1.3

Calculate readability scores for Japanese texts.

Text readability calculator for Japanese learners 🇯🇵

jReadability allows python developers to calculate the readability of Japanese text using the model developed by Jae-ho Lee and Yoichiro Hasebe in Introducing a readability evaluation system for Japanese language education and Readability measurement of Japanese texts based on levelled corpora. Note that this is not an official implementation.

Demo

You can play with an interactive demo here.

Installation

pip install jreadability

Quickstart

from jreadability import compute_readability

# "Good morning! The weather is nice today."
text = 'おはようございます！今日は天気がいいですね。' 

score = compute_readability(text)

print(score) # 6.438000000000001

Readability scores

Level	Readability score range
Upper-advanced	[0.5, 1.5)
Lower-advanced	[1.5, 2.5)
Upper-intermediate	[2.5, 3.5)
Lower-intermediate	[3.5, 4.5)
Upper-elementary	[4.5, 5.5)
Lower-elementary	[5.5, 6.5)

Note that this readability calculator is specifically for non-native speakers learning to read Japanese. This is not to be confused with something like grade level or other readability scores meant for native speakers.

Model

readability = {mean number of words per sentence} * -0.056
            + {percentage of kango} * -0.126
            + {percentage of wago} * -0.042
            + {percentage of verbs} * -0.145
            + {percentage of particles} * -0.044
            + 11.724

* "kango" (漢語) means Japanese word of Chinese origin while "wago" (和語) means native Japanese word.

Note on model consistency

The readability scores produced by this python package tend to differ slightly from the scores produced on the official jreadability website. This is likely due to the version difference in UniDic between these two implementations as this package uses UniDic 2.1.2 while theirs uses UniDic 2.2.0. This issue may be resolved in the future.

Batch processing

jreadability makes use of fugashi's tagger under the hood and initializes a new tagger everytime compute_readability is invoked. If you are processing a large number of texts, it is recommended to initialize the tagger first on your own, then pass it as an argument to each subsequent compute_readability call.

from fugashi import Tagger

texts = [...]

tagger = Tagger()

for text in texts:
    
    score = compute_readability(text, tagger) # fast :D
    #score = compute_readability(text) # slow :'(
    ...

Other implementations

The official jReadability implementation can be found on jreadability.net

A node.js implementation can also be found here.