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google/mozc

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2,833 stars·455 forks·C++·other·4 views

Mozc

Mozc is a Japanese input method engine that converts romanized or kana keystrokes into Japanese kanji, kana, and mixed text with predictive conversion. It functions as a cross-platform input method framework, compiling the same engine into platform-specific binaries for Android, Linux, macOS, and Windows.

The engine combines a dictionary-based segmentation system with a hybrid of rule-based and statistical language models to determine word boundaries and predict character sequences. A prefix-tree structure enables real-time, context-aware conversion suggestions as the user types, while a key-event rewriting pipeline transforms raw keystrokes into composable text segments before passing them to the conversion engine.

Mozc manages input through a deterministic state machine that switches between hiragana, katakana, half-width, and direct ASCII modes during composition. The system separates the input method frontend from the conversion engine backend using inter-process communication, keeping the engine platform-independent while allowing platform-specific user interfaces.

Features

  • Japanese Text Converters - Converts typed romanized or kana syllables into Japanese kanji, kana, and mixed text using a predictive engine.
  • Prediction Engines - Uses statistical language models to predict and convert typed syllables into Japanese characters and words.
  • Hybrid Language Models - Combines hand-crafted grammatical rules with a statistical n-gram model for predicting kanji and kana output.
  • Morpheme Segmentation Dictionaries - Splits typed romanized or kana input into morphemes using a precompiled dictionary for accurate conversion.
  • Input Method Engine Compilers - Compiles the input method engine into platform-specific binaries for Android, Linux, macOS, and Windows.
  • Predictive Conversion Tries - Builds a trie of word and phrase candidates from a language model for real-time Japanese text conversion.
  • Input Method Text Engines - Converts romanized or kana keystrokes into Japanese kanji, kana, and mixed text with predictive conversion.
  • Japanese Input Mode Toggles - Toggles between hiragana, katakana, half-width, and direct ASCII input modes during composition.
  • Keystroke Rewriting Pipelines - Intercepts and transforms raw keystrokes into composable text segments for complex Japanese input sequences.
  • Input Mode State Machines - Manages a deterministic state machine switching between hiragana, katakana, half-width, and ASCII modes.
  • Cross-Platform Build Systems - Uses a unified build configuration to compile the same engine source into native binaries for multiple platforms.
  • Keyboard Input Modes - Toggles between hiragana, katakana, half-width, and direct ASCII input modes during text composition.
  • Client-Server Architectures - Separates the IME frontend from the conversion engine backend via inter-process communication.
  • Cross-Platform Development - Builds and compiles a Japanese input method engine into platform-specific binaries for multiple operating systems.
  • Cross-Platform Frameworks - Provides a build system that compiles the same input method engine into platform-specific binaries for multiple operating systems.

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Open-source alternatives to Mozc

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Frequently asked questions

What does google/mozc do?

Mozc is a Japanese input method engine that converts romanized or kana keystrokes into Japanese kanji, kana, and mixed text with predictive conversion. It functions as a cross-platform input method framework, compiling the same engine into platform-specific binaries for Android, Linux, macOS, and Windows.

What are the main features of google/mozc?

The main features of google/mozc are: Japanese Text Converters, Prediction Engines, Hybrid Language Models, Morpheme Segmentation Dictionaries, Input Method Engine Compilers, Predictive Conversion Tries, Input Method Text Engines, Japanese Input Mode Toggles.

What are some open-source alternatives to google/mozc?

Open-source alternatives to google/mozc include: amzxyz/rime_wanxiang — This project is a CJK input method framework and configuration set designed for the Rime input engine. It provides a… osfans/trime — Trime is a customizable text input framework and engine based on the Rime input method. It enables the entry of… fcitx5-android/fcitx5-android — Fcitx5 Android is an input method manager that brings the Fcitx5 framework to Android, enabling multilingual text… dotnet/machinelearning — This is a cross-platform framework for building, training, and deploying custom machine learning models within the… apache/predictionio — PredictionIO is a machine learning server designed for the deployment of predictive models to transform raw data into… emacs-evil/evil — Evil is a modal editing framework and state-machine layer for the Emacs text editor. It functions as a modal text…