Visual novel Japanese reading statistics
How hard is Yoake Mae yori Ruri Iro na to read in Japanese?
夜明け前より瑠璃色な
Aggregate vocabulary, kanji, length, and reading-profile data from the DokiDokiDict recommender corpus.
Japanese reading profile
This indexed edition contains 1,007,816 Japanese characters across 64,360 sentences. By length it is at approximately the 66th percentile of the 76 indexed visual novels. Its vocabulary breadth is at approximately the 58th percentile within the same group.
Those numbers describe the text, not your personal comprehension. A long work can contain more unique vocabulary while still becoming comfortable through repetition. DokiDokiDict's recommender uses your own known words and simulates the work sentence by sentence instead of assigning one universal level.
Also known as: Brighter than Dawning Blue, yoakena, keyorina, akeruri, yoriruri
Vocabulary coverage by starting level
This table uses the same analysis scale as the VN staircase. The first percentage is coverage before starting. The second is coverage of the unread remainder after the first 30% has been treated as read.
| Default VN words known | Starting coverage | Remaining coverage after 30% |
|---|---|---|
| 500 | 66.7% | 84.7% |
| 1,000 | 76.3% | 85.6% |
| 2,000 | 84.8% | 88.2% |
| 3,000 | 88.8% | 90.9% |
| 5,000 | 92.7% | 94.0% |
| 10,000 | 96.8% | 97.4% |
| 15,000 | 98.3% | 98.7% |
| 20,000 | 99.1% | 99.3% |
You would need to know roughly the 3,515 most frequent Default VN words to begin at 90% coverage, or roughly the top 7,247 for 95%.
How to read this: the vocabulary axis uses the Default VN frequency list. Grammar, punctuation, and proper names are excluded, while twenty frequent local words are treated as manageable. The 30% simulation counts a word as learned after four sightings separated by at least five pages. It models exposure and recognition, not guaranteed acquisition.
Works with a similar aggregate profile
These are nearby works of the same type by indexed length, vocabulary breadth, and kanji breadth. Similar statistics do not necessarily mean similar prose or subject matter.
See whether it fits your vocabulary
Import your DokiDokiDict history, Anki cards, built-in SRS deck, or manually known words, then simulate this work against what you actually know.