Skip to main content

Lightweight Japanese text-to-IPA phoneme converter extracted from misaki

Project description

misaki-ja-lightning ⚡

Lightweight Japanese text-to-IPA phoneme converter extracted from the misaki library. This package contains only the Japanese G2P (grapheme-to-phoneme) functionality with minimal dependencies.

Features

  • 🇯🇵 Convert Japanese text (hiragana, katakana, kanji) to IPA phonemes
  • 🔢 Convert numbers to Japanese kana
  • ⚡ Lightning-fast with minimal dependencies
  • 🎯 Focused on Japanese language only
  • 🔧 Uses pyopenjtalk for accurate phoneme conversion

Installation

pip install misaki-ja-lightning

Usage

Basic G2P Conversion

from misaki_ja_lightning import JAG2P

# Initialize the converter
g2p = JAG2P()

# Convert Japanese text to IPA phonemes
text = "こんにちは、世界"
phonemes, tokens = g2p(text)

print(phonemes)  # IPA phoneme string with pitch information

Number to Kana Conversion

from misaki_ja_lightning import Convert, ConvertKanji

# Convert Arabic numbers to Japanese
result = Convert(12345, 'hiragana')
print(result)  # いちまんにせんさんびゃくよんじゅうご

# Convert to kanji
result = Convert(12345, 'kanji')
print(result)  # 一万二千三百四十五

# Convert to romaji
result = Convert(12345, 'romaji')
print(result)  # ichi man ni sen san byaku yon juu go

# Supported formats: 'hiragana', 'kanji', 'romaji'
# Note: 'katakana' is not supported in num2kana module

# Convert kanji numbers back to Arabic
number = ConvertKanji("一万二千三百四十五")
print(number)  # 12345

Token-level Processing

from misaki_ja_lightning import JAG2P

g2p = JAG2P()
phonemes, tokens = g2p("今日は良い天気ですね")

for token in tokens:
    print(f"Text: {token.text}")
    print(f"Phonemes: {token.phonemes}")
    print(f"Tag: {token.tag}")
    print(f"Pitch: {token._.pitch}")
    print("---")

What's Included

This lightweight package includes only:

  • ja.py - Japanese G2P converter using pyopenjtalk
  • num2kana.py - Number to Japanese kana converter
  • token.py - Token data structure

Differences from Original Misaki

  • ✅ Japanese-only (removed other languages)
  • ✅ Removed cutlet dependency
  • ✅ Removed addict dependency
  • ✅ Simplified token structure
  • ✅ Only pyopenjtalk version (no cutlet option)
  • ✅ Minimal dependencies

Requirements

  • Python >= 3.8
  • pyopenjtalk >= 0.3.0

License

MIT License (inherited from original misaki library)

Credits

This package is extracted from misaki by hexgrad. All credit for the original implementation goes to the misaki authors.

The num2kana module is based on Convert-Numbers-to-Japanese by Greatdane (MIT License).

Related Projects

Use Cases

Perfect for:

  • Text-to-speech applications
  • Japanese language learning tools
  • Phoneme-based synthesis
  • Lightweight Japanese text processing

Support

For issues and questions, please visit the GitHub Issues page.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

misaki_ja_lightning-0.1.0.tar.gz (16.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

misaki_ja_lightning-0.1.0-py3-none-any.whl (11.9 kB view details)

Uploaded Python 3

File details

Details for the file misaki_ja_lightning-0.1.0.tar.gz.

File metadata

  • Download URL: misaki_ja_lightning-0.1.0.tar.gz
  • Upload date:
  • Size: 16.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.2

File hashes

Hashes for misaki_ja_lightning-0.1.0.tar.gz
Algorithm Hash digest
SHA256 de1a509c74526327ee7534fbaa95ae90a09275a78242af103e04ac17fc8e68a8
MD5 a14cf10f5e389df6ad7f77319bd99d0a
BLAKE2b-256 0a59f6a60ed4b726e38340ad75b5dcf86b4196554fea182ad7dd55a8293b6ac3

See more details on using hashes here.

File details

Details for the file misaki_ja_lightning-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for misaki_ja_lightning-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 6c3a3dae1ff19e4996e3b946a9563bf720d4f59d8dbbf77ccba6e5d39947d9ac
MD5 ae50fc4989f4788c474afea02acfaca6
BLAKE2b-256 81888c5582ed51dd4abca86d08f19e9683de61a1017c7dcbe7f4bda65572a7a5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page