Cutlet is a tool to convert Japanese to romaji. Check out the interactive demo! Also see the docs and the original blog post.

issueを英語で書く必要はありません。

Features:

• support for Modified Hepburn, Kunreisiki, Nihonsiki systems
• custom overrides for individual mappings
• custom overrides for specific words
• built in exceptions list (Tokyo, Osaka, etc.)
• uses foreign spelling when available in UniDic
• proper nouns are capitalized
• slug mode for url generation

Things not supported:

• traditional Hepburn n-to-m: Shimbashi
• macrons or circumflexes: Tōkyō, Tôkyô
• passport Hepburn: Satoh (but you can use an exception)
• hyphenating words
• Traditional Hepburn in general is not supported

Internally, cutlet uses fugashi, so you can use the same dictionary you use for normal tokenization.

Cutlet can be installed through pip as usual.

pip install cutlet

Note that if you don't have a MeCab dictionary installed you'll also have to install one. If you're just getting started unidic-lite is a good choice.

pip install unidic-lite

A command-line script is included for quick testing. Just use cutlet and each line of stdin will be treated as a sentence. You can specify the system to use (hepburn, kunrei, nippon, or nihon) as the first argument.

$ cutlet
ローマ字変換プログラム作ってみた。
Roma ji henkan program tsukutte mita.

In code:

import cutlet
katsu = cutlet.Cutlet()
katsu.romaji("カツカレーは美味しい")
# => 'Cutlet curry wa oishii'
# you can print a slug suitable for urls
katsu.slug("カツカレーは美味しい")
# => 'cutlet-curry-wa-oishii'
# You can disable using foreign spelling too
katsu.use_foreign_spelling = False
katsu.romaji("カツカレーは美味しい")
# => 'Katsu karee wa oishii'
# kunreisiki, nihonsiki work too
katu = cutlet.Cutlet('kunrei')
katu.romaji("富士山")
# => 'Huzi yama'
# comparison
nkatu = cutlet.Cutlet('nihon')
sent = "彼女は王への手紙を読み上げた。"
katsu.romaji(sent)
# => 'Kanojo wa ou e no tegami wo yomiageta.'
katu.romaji(sent)
# => 'Kanozyo wa ou e no tegami o yomiageta.'
nkatu.romaji(sent)
# => 'Kanozyo ha ou he no tegami wo yomiageta.'

• kakasi: Historically important, but not updated since 2014.
• pykakasi: self contained, it does segmentation on its own and uses its own dictionary.