Name: Suzume
Author: libraz

Question 1

What is Suzume?

Accepted Answer

Suzume is a lightweight, feature-driven Japanese tokenizer that runs on WebAssembly. Unlike dictionary-based analyzers like MeCab, it works without large dictionary files and is robust to unknown words. It runs in browsers, Node.js, Deno, and Bun.

Question 2

How does Suzume handle unknown words?

Accepted Answer

Suzume generates candidates from character patterns (kanji sequences, katakana sequences, alphanumeric compounds) and evaluates them alongside dictionary entries using Viterbi algorithm. This makes it robust to neologisms and domain-specific terms.

Question 3

Can I use Suzume in the browser?

Accepted Answer

Yes, Suzume runs entirely in the browser via WebAssembly. No server required. You can load it from npm or directly from a CDN like esm.sh. The entire package is under 350KB gzipped.

Question 4

How do I add custom words to Suzume?

Accepted Answer

Use loadUserDictionary() to add custom words at runtime. Format: "word,pos" (e.g., "ChatGPT,noun"). You can add brand names, technical terms, or domain-specific vocabulary without rebuilding the dictionary.

Question 5

What is the difference between Suzume and MeCab?

Accepted Answer

MeCab requires large dictionary files (50MB+) and server-side installation. Suzume uses feature-based analysis with a minimal dictionary, runs on WebAssembly in the browser, and handles unknown words gracefully. Choose Suzume for client-side processing without server infrastructure.

Question 6

How is Suzume different from kuromoji.js?

Accepted Answer

kuromoji.js requires downloading a 20MB+ dictionary on first load, causing slow initial page loads. Suzume is under 350KB gzipped and loads instantly. Suzume also handles unknown words better and has a simpler API.

Question 7

Can I use Suzume for SEO keyword extraction?

Accepted Answer

Yes, Suzume can extract nouns and compound words from Japanese text, making it ideal for auto-tagging blog posts, generating hashtags, or building keyword analysis tools - all without server infrastructure.

Question 8

Is Suzume suitable for production use?

Accepted Answer

Yes, Suzume is production-ready. It is compiled from C++ to WebAssembly for near-native performance, includes full TypeScript support, and works in all modern browsers, Node.js, Deno, and Bun.

Question 9

Does Suzume work offline?

Accepted Answer

Yes, once loaded, Suzume works completely offline. All processing happens locally in the browser or runtime. No API calls or internet connection required after initial load.

Question 10

How do I install Suzume?

Accepted Answer

Install via npm: npm install @libraz/suzume. Then import and use: const { Suzume } = await import("@libraz/suzume"); const suzume = await Suzume.create(); const result = suzume.analyze("日本語テキスト");

	MeCab	Suzume
アプローチ	辞書駆動型	特徴量駆動型
辞書	50MB以上（必須）	最小限（WASM含め約300KB）
未知語	文字種にフォールバック	パターンベースの候補生成
複合語	辞書に基づき分割	文字種ヒューリスティクスで結合
対象	サーバーサイド、学術用途	ブラウザ、リアルタイム、クライアントサイド

MeCab	Suzume
名詞,一般	NOUN
名詞,固有名詞,地域	NOUN
名詞,サ変接続	NOUN
名詞,副詞可能	NOUN
動詞,自立	VERB
動詞,非自立	VERB

ユースケース	推奨
ブラウザ / クライアントサイドアプリ	Suzume — サーバー不要
検索インデックス / タグ抽出	Suzume — 複合語結合がむしろ有利
学術研究 / コーパス分析	MeCab — 最大精度と品詞の詳細
リアルタイム UI（入力中の処理）	Suzume — 高速、ネットワーク遅延なし
正確な複合語の分割	MeCab — 辞書駆動の境界判定
未知語・現代語の処理	Suzume — 未登録語にも頑健

MeCab との違い

設計思想

意図的な違い

1. 漢字複合語の結合

2. カタカナ複合語の結合

3. 数字＋助数詞の結合

4. 日付の結合

5. ナイ形容詞の一体処理

6. スラング・現代語の形容詞対応

Suzume が MeCab より優れるケース

品詞の修正

スラング・現代語

助詞の誤分類

制約

結合された複合語の分割不可

文脈依存の品詞分類

品詞の粒度

使い分けの指針

MeCab との違い ​

設計思想 ​

意図的な違い ​

1. 漢字複合語の結合 ​

2. カタカナ複合語の結合 ​

3. 数字＋助数詞の結合 ​

4. 日付の結合 ​

5. ナイ形容詞の一体処理 ​

6. スラング・現代語の形容詞対応 ​

Suzume が MeCab より優れるケース ​

品詞の修正 ​

スラング・現代語 ​

助詞の誤分類 ​

制約 ​

結合された複合語の分割不可 ​

文脈依存の品詞分類 ​

品詞の粒度 ​

使い分けの指針 ​