Fast phonemizer with rule-based G2P (Grapheme-to-Phoneme) prediction. Pure JavaScript implementation with no native dependencies.
Inspired by ttstokenizer
- ⚡ Lightning fast - Pure rule-based processing, no ML overhead
- 🎯 Intelligent compound word support - Automatic decomposition of complex words
- 📚 Comprehensive dictionary - 125,000+ word pronunciations
- 🧠 Smart rule-based G2P - Advanced phonetic rules for unknown words
- 🌍 Multiple formats - IPA, ARPABET, and Zhuyin output
- 🌐 Modular multilingual support - G2P models are modularize load
- 💻 Pure JavaScript - No native dependencies, works everywhere
- 🔧 Simple API - Easy to integrate and use
npm install phonemize
import { phonemize, toIPA, toARPABET } from 'phonemize'
// Default IPA output
console.log(phonemize('Hello world!'))
// Output: həˈɫoʊ ˈwɝɫd!
// ARPABET format
console.log(toARPABET('Hello world!'))
// Output: HH AX EL1 OW W1 ER EL D!
For different language support needs, you can use preset modules:
// Default: English only
import { phonemize } from 'phonemize'
// Chinese + English
import { phonemize } from 'phonemize/zh'
// All languages (English + Chinese + Japanese + Korean + Russian)
import { phonemize } from 'phonemize/all'
// Clean
Convert text to phonemes.
phonemize('Hello world!') // IPA string
phonemize('Hello world!', { returnArray: true }) // IPA array
Options:
returnArray
(boolean): Return array instead of stringformat
('ipa' | 'arpabet'): Output formatstripStress
(boolean): Remove stress markersseparator
(string): Phoneme separator (default: ' ')anyAscii
(boolean): Enable multilingual support via anyAscii transliteration
Convert text to IPA phonemes.
toIPA('Hello world!') // "həˈɫoʊ ˈwɝɫd!"
Convert text to ARPABET phonemes.
toARPABET('Hello world!') // "HH AX L OW1 W ER1 L D!"
Convert text to Zhuyin (Bopomofo / 注音) format.
This function is specifically designed for Chinese text. Non-Chinese text will be phonemized to IPA as a fallback.
Note: The output format is Zhuyin + tone number
(e.g., ㄓㄨㄥ1 ㄨㄣ2
), which is optimized for Kokoro.
import { toZhuyin } from 'phonemize';
toZhuyin('中文'); // "ㄓㄨㄥ1 ㄨㄣ2"
toZhuyin('你好世界'); // "ㄋㄧ3 ㄏㄠ3 ㄕ4 ㄐㄧㄝ4"
toZhuyin('中文 and English'); // "ㄓㄨㄥ1 ㄨㄣ2 ænd ˈɪŋɡlɪʃ"
Register a G2P processor for multilingual support.
import { useG2P } from 'phonemize'
import ChineseG2P from 'phonemize/zh-g2p'
import JapaneseG2P from 'phonemize/ja-g2p'
// Register G2P processors
useG2P(new ChineseG2P())
useG2P(new JapaneseG2P())
// Now phonemize can handle Chinese and Japanese text
phonemize('你好') // → ni˧˥ xɑʊ˨˩˦
phonemize('こんにちは', { anyAscii: true }) // → konnitɕiwa
import { addPronunciation } from 'phonemize'
// Add custom word pronunciation
addPronunciation('myword', 'ˈmaɪwərd') // Can be IPA or ARPABET
console.log(phonemize('myword')) // "ˈmaɪwərd"
import { Tokenizer, createTokenizer } from 'phonemize'
// Create custom tokenizer
const tokenizer = createTokenizer({
format: 'ipa',
stripStress: true,
separator: '-'
})
// Tokenize with detailed info
const tokens = tokenizer.tokenizeToTokens('Hello world!')
// [
// { phoneme: "həɫoʊ", word: "Hello", position: 0 },
// { phoneme: "wɝɫd", word: "world", position: 6 }
// ]
Numbers are automatically converted to words:
phonemize('I have 123 apples')
// "ˈaɪ ˈhæv ˈwən ˈhəndɝd ˈtwɛni ˈθɹi ˈæpəɫz"
Common abbreviations are expanded:
phonemize('Dr. Smith and Mr. Johnson')
// "ˈdɑktɝ ˈsmɪθ ˈænd ˈmɪstɝ ˈdʒɑnsən"
Special handling for currency and dates:
phonemize('15 dollars in 2023')
// "ˈfɪfˈtin ˈdɑɫɝz ˈɪn ˈtwɛni ˈtwɛni ˈθɹi"
- Dictionary lookup: O(1) - Instant for known words
- Rule-based processing: Extremely fast, no model loading
- Compound decomposition: Efficient balanced search algorithm
- Memory efficient: Compressed JSON dictionaries only
- Zero startup time: No model initialization required
Typical performance: >10000 words/second on modern hardware.
- Language Detection - Detect language before anyAscii conversion (if enabled)
- anyAscii Transliteration - Convert non-Latin scripts to ASCII (if enabled)
- Dictionary Lookup - Check for exact word match
- Multilingual Processing - Handle Chinese, Japanese, Korean, etc.
- Compound Detection - Intelligent decomposition of compound words
- Multi-Compound Handling - Special processing for very long compounds
- Rule-Based G2P - Apply phonetic rules for unknown words
Note: The rule based G2P is LLM generated, may error generate. Best practice is use custom pronunciation for unknown words.
Standard IPA symbols for English phonemes with stress marks.
CMU ARPABET phoneme set with stress numbers (0,1,2).
# Install dependencies
yarn
# Compile TypeScript and dictionaries
yarn build
# Run tests
yarn test
MIT