Language Support

kokorog2p supports multiple languages with varying levels of functionality.

Language Support Overview

Language	Code	Dictionary	Fallback	Special Features
English (US)	en-us	100k+ entries	espeak-ng	POS tagging, stress, numbers
English (GB)	en-gb	100k+ entries	espeak-ng	POS tagging, stress, numbers
German	de	738k+ entries	espeak-ng	Phonological rules, numbers
French	fr	Gold dictionary	espeak-ng	Numbers, liaison rules
Spanish	es	Rule-based	espeak-ng/goruut	Phonological rules, numbers
Italian	it	Rule-based	espeak-ng/goruut	Phonological rules, gemination
Portuguese	pt	Rule-based	—	Phonological rules, nasalization
Czech	cs	Rule-based	espeak-ng/goruut	Phonological rules
Chinese	zh	—	pypinyin	Tone sandhi, pinyin
Japanese	ja	—	pyopenjtalk	Mora-based, pitch accent
Korean	ko	—	MeCab	Phonological rules, liaison
Hebrew	he	—	phonikud	Nikud handling, stress
Mixed	multilingual	Auto-detect	lingua-py	17+ languages, word-level detection

English (en-us, en-gb)

English G2P uses a two-tier dictionary system with spaCy for POS tagging.

Features

• Gold dictionary: 50k+ high-confidence entries

• Silver dictionary: Additional 50k+ entries

• POS-aware pronunciation: Different pronunciations based on part of speech

• Stress assignment: Primary and secondary stress markers

• Number handling: Cardinals, ordinals, currency

• Contraction support: Proper handling of “can’t”, “won’t”, etc.

Usage

from kokorog2p.en import EnglishG2P

# US English
g2p_us = EnglishG2P(
    language="en-us",
    use_espeak_fallback=True,
    use_spacy=True,
    spacy_model="en_core_web_md",  # default
)

# British English
g2p_gb = EnglishG2P(
    language="en-gb",
    use_espeak_fallback=True,
    use_spacy=True,
    spacy_model="en_core_web_md",  # default
)

# Optional: select a different spaCy English model
g2p_sm = EnglishG2P(language="en-us", use_spacy=True, spacy_model="en_core_web_sm")

Examples

from kokorog2p import phonemize

# Context-dependent pronunciation
print(phonemize("I read a book.", language="en-us"))
# → ˈaɪ ɹˈɛd ə bˈʊk.

print(phonemize("I will read tomorrow.", language="en-us"))
# → ˈaɪ wɪl ɹˈid təmˈɑɹO.

# Numbers and currency
print(phonemize("I paid $1,234.56 for it.", language="en-us"))
# → aɪ pˈeɪd wʌn θˈaʊzənd tˈu hˈʌndɹəd...

German (de)

German G2P uses a large dictionary (738k+ entries from Olaph) with rule-based fallback.

Features

• Large dictionary: 738k+ entries with stress markers

• Phonological rules:

  • Final obstruent devoicing (Auslautverhärtung)

  • ich-Laut [ç] vs ach-Laut [x] alternation

  • Word-initial sp/st → [ʃp]/[ʃt]

  • Vowel length rules

  • Schwa in unstressed syllables

• Number handling: Cardinals, ordinals, years, currency

• Regional variants: de-de, de-at, de-ch

Usage

from kokorog2p.de import GermanG2P

g2p = GermanG2P(
    language="de-de",
    use_espeak_fallback=True,
    strip_stress=True
)

Examples

from kokorog2p import phonemize

# Basic phonemization
print(str(phonemize("Guten Tag", language="de")))
# → ɡuːtn̩ taːk

# Phonological rules
print(str(phonemize("ich", language="de")))      # → ɪç (ich-Laut)
print(str(phonemize("ach", language="de")))      # → ax (ach-Laut)
print(str(phonemize("Tag", language="de")))      # → taːk (final devoicing)

# Numbers
print(str(phonemize("Ich habe 42 Euro.", language="de")))
# → ɪç haːbə t͡svaɪ̯ʊntfɪɐ̯t͡sɪç ɔɪ̯ʁo.

French (fr)

French G2P uses a gold dictionary with espeak-ng fallback.

Features

• Gold dictionary: High-quality French pronunciations

• Number handling: Cardinals, ordinals, currency

• espeak-ng fallback: For out-of-vocabulary words

Usage

from kokorog2p.fr import FrenchG2P

g2p = FrenchG2P(
    language="fr-fr",
    use_espeak_fallback=True
)

Examples

from kokorog2p import phonemize

print(phonemize("Bonjour le monde", language="fr"))
# → bɔ̃ʒuʁ lə mɔ̃d

print(phonemize("J'ai vingt et un ans.", language="fr"))
# → ʒɛ vɛ̃t e œ̃ ɑ̃.

Czech (cs)

Czech G2P is entirely rule-based with comprehensive phonological rules.

Features

• Rule-based phonology:

  • Palatalization (d+i → ɟ, t+i → c, n+i → ɲ)

  • Long vowels (á → aː, í → iː, etc.)

  • ř phoneme [r̝]

  • ch digraph → [x]

  • Final devoicing

  • Voicing assimilation

• No dictionary required: Works with any Czech text

Usage

from kokorog2p.cs import CzechG2P

g2p = CzechG2P(language="cs-cz")

Examples

from kokorog2p import phonemize

print(phonemize("Dobrý den", language="cs"))
# → dobriː dɛn

print(phonemize("Praha", language="cs"))
# → praɦa

# Palatalization
print(phonemize("děti", language="cs"))
# → ɟɛcɪ

 # ř phoneme
 print(phonemize("řeka", language="cs"))
 # → r̝ɛka

Spanish (es)

Spanish G2P is rule-based with comprehensive phonological rules for both European and Latin American dialects.

Features

• Rule-based phonology:

  • 5 pure vowels (a, e, i, o, u)

  • Stress prediction (penultimate for vowel-ending, final for consonant-ending)

  • Palatal sounds: ñ [ɲ], ll [ʎ] or [j]

  • Jota: j/g+e/i [x]

  • Theta: z/c+e/i [θ] (European) or [s] (Latin American)

  • Tap vs trill: r [ɾ] vs rr [r]

• Dialect support: es (European), la (Latin American)

• Number handling: Cardinals, ordinals, currency

Usage

from kokorog2p.es import SpanishG2P

g2p = SpanishG2P(
    language="es",
    dialect="es"  # or "la" for Latin American
)

Examples

from kokorog2p import phonemize

print(phonemize("Hola mundo", language="es"))
# → ola mundo

# Phonological features
print(phonemize("año", language="es"))      # → aɲo
print(phonemize("calle", language="es"))    # → kaʎe or kaje
print(phonemize("perro", language="es"))    # → pero (trilled r)

Italian (it)

Italian G2P uses rule-based phonology with predictable stress and gemination handling.

Features

• Rule-based phonology:

  • 5 pure vowels (a, e, i, o, u) - no reduction

  • Predictable stress (usually penultimate)

  • Gemination (double consonants) preservation

  • Palatals: gn [ɲ], gli [ʎ]

  • Affricates: z [ʦ/ʣ], c/ci [ʧ], g/gi [ʤ]

  • Context-sensitive c/g pronunciation

• Stress marking: Automatic stress detection from accents

• Number handling: Cardinals, ordinals

Usage

from kokorog2p.it import ItalianG2P

g2p = ItalianG2P(
    language="it-it",
    mark_stress=True,
    mark_gemination=True
)

Examples

from kokorog2p import phonemize

print(phonemize("Ciao mondo", language="it"))
# → ʧao mondo

# Gemination
print(phonemize("anno", language="it"))     # → anːo
print(phonemize("fatto", language="it"))    # → fatːo

# Palatals
print(phonemize("gnocchi", language="it"))  # → ɲɔkːi
print(phonemize("figlio", language="it"))   # → fiʎo

Portuguese (pt)

Portuguese G2P supports Brazilian Portuguese with comprehensive phonological rules.

Features

• Rule-based phonology:

  • 7 oral vowels (a, e, ɛ, i, o, ɔ, u)

  • 5 nasal vowels (ã, ẽ, ĩ, õ, ũ)

  • Nasal diphthongs

  • Palatalization: lh [ʎ], nh [ɲ], x/ch [ʃ]

  • Affrication: t+i [ʧ], d+i [ʤ] (Brazilian)

  • Sibilants: s [s/z], x [ʃ], z [z]

  • Liquids: r [ʁ/x/h], rr [ʁ/x], single r [ɾ]

• Dialect: Brazilian Portuguese (pt-br)

• Stress marking: Automatic stress assignment

Usage

from kokorog2p.pt import PortugueseG2P

g2p = PortugueseG2P(
    language="pt-br",
    mark_stress=True,
    affricate_ti_di=True  # Brazilian feature
)

Examples

from kokorog2p import phonemize

print(phonemize("Olá mundo", language="pt"))
# → ola mundo

# Nasal vowels
print(phonemize("mãe", language="pt"))      # → mãj̃
print(phonemize("pão", language="pt"))      # → pãw̃

# Affrication (Brazilian)
print(phonemize("tia", language="pt"))      # → ʧia
print(phonemize("dia", language="pt"))      # → ʤia

Chinese (zh)

Chinese G2P uses jieba for tokenization and pypinyin for phoneme conversion.

Features

• Jieba tokenization: Chinese word segmentation

• Pypinyin conversion: Pinyin to IPA

• Tone sandhi: Automatic tone changes

• cn2an: Number to Chinese conversion

• Punctuation mapping: Chinese to Western punctuation

Usage

from kokorog2p.zh import ChineseG2P

g2p = ChineseG2P(
    language="zh",
    version="1.1"
)

Examples

from kokorog2p import phonemize

print(phonemize("你好世界", language="zh"))
# → nǐ hǎo shì jiè (with tone markers)

Japanese (ja)

Japanese G2P uses pyopenjtalk for text analysis and mora-based phoneme generation.

Features

• pyopenjtalk: Full Japanese text analysis

• Mora-based: Phonemes aligned with mora structure

• Pitch accent: Automatic pitch accent assignment

• Number handling: Japanese numerals

Usage

from kokorog2p.ja import JapaneseG2P

g2p = JapaneseG2P(
    language="ja",
    version="pyopenjtalk"
)

Examples

from kokorog2p import phonemize

print(phonemize("こんにちは", language="ja"))
# → koɴɲit͡ɕiha

print(phonemize("世界", language="ja"))
# → sekai

Korean (ko)

Korean G2P uses MeCab-based morphological analysis with comprehensive phonological rules.

Features

• MeCab integration: Korean morphological analysis

• Phonological rules:

  • Consonant assimilation

  • Palatalization

  • Tensification

  • Aspiration

  • Liaison (연음)

  • Final consonant neutralization

• Hanja support: Sino-Korean character handling

• Number handling: Korean numerals

Usage

from kokorog2p.ko import KoreanG2P

g2p = KoreanG2P(
    language="ko-kr",
    use_mecab=True
)

Examples

from kokorog2p import phonemize

print(phonemize("안녕하세요", language="ko"))
# → annjʌŋhasejo

# Phonological rules
print(phonemize("학교", language="ko"))     # → hakk͈jo (tensification)
print(phonemize("받침", language="ko"))     # → patʃʰim (palatalization)

Hebrew (he)

Hebrew G2P uses phonikud for nikud-based phonemization.

Features

• phonikud integration: Hebrew nikud to IPA conversion

• Nikud handling: Processes diacritical marks for vowels

• Stress prediction: Automatic stress assignment

• Modern Hebrew: Optimized for contemporary pronunciation

Usage

from kokorog2p.he import HebrewG2P

g2p = HebrewG2P(
    language="he-il",
    preserve_punctuation=True,
    preserve_stress=True
)

Examples

from kokorog2p import phonemize

# Requires nikud (diacritical marks)
print(phonemize("שָׁלוֹם", language="he"))
# → ʃalom

print(phonemize("עִבְרִית", language="he"))
# → ivʁit

Mixed-Language Support

kokorog2p can automatically detect and handle texts that mix multiple languages, routing each word to the appropriate G2P engine.

Features

• Automatic detection: Word-level language detection using lingua-py

• High accuracy: >90% accuracy for words with 5+ characters

• Caching: Detection results cached for performance

• Configurable threshold: Control detection sensitivity

• Graceful degradation: Falls back to primary language without lingua-py

• 17+ languages: Support for major world languages

Supported Languages

• English (en-us, en-gb)

• German (de)

• French (fr)

• Spanish (es)

• Italian (it)

• Portuguese (pt)

• Japanese (ja)

• Chinese (zh)

• Korean (ko)

• Hebrew (he)

• Czech (cs)

• Dutch (nl)

• Polish (pl)

• Russian (ru)

• Arabic (ar)

• Hindi (hi)

• Turkish (tr)

Usage

from kokorog2p import phonemize
from kokorog2p.multilang import preprocess_multilang

text = "Das Meeting war great!"
overrides = preprocess_multilang(
    text,
    default_language="de",
    allowed_languages=["de", "en-us"],
)

result = phonemize(text, lang="de", overrides=overrides, result_type="result")

Examples

German with English:

from kokorog2p import phonemize
from kokorog2p.multilang import preprocess_multilang

text = "Ich gehe zum Meeting. Let's discuss the Roadmap!"
overrides = preprocess_multilang(
    text,
    default_language="de",
    allowed_languages=["de", "en-us"],
)
result = phonemize(text, lang="de", overrides=overrides, result_type="result")
print(result.phonemes)

English with German:

overrides = preprocess_multilang(
    "Hello, mein Freund! This is wunderbar.",
    default_language="en-us",
    allowed_languages=["en-us", "de"],
)
result = phonemize(
    "Hello, mein Freund! This is wunderbar.",
    language="en-us",
    overrides=overrides)
)
print(result.phonemes)

Multiple languages:

overrides = preprocess_multilang(
    "Bonjour! The Meeting ist wichtig.",
    default_language="fr",
    allowed_languages=["fr", "en-us", "de"],
)
result = phonemize(
    "Bonjour! The Meeting ist wichtig.",
    language="fr",
    overrides=overrides,
)
print(result.phonemes)

Configuration

Confidence threshold:

from kokorog2p.multilang import preprocess_multilang

# Conservative (higher confidence required)
overrides = preprocess_multilang(
    "Das Meeting ist wichtig",
    default_language="de",
    allowed_languages=["de", "en-us"],
    confidence_threshold=0.9,  # Default: 0.7
)

# Aggressive (lower confidence required)
overrides = preprocess_multilang(
    "Das Meeting ist wichtig",
    default_language="de",
    allowed_languages=["de", "en-us"],
    confidence_threshold=0.5,
)

How It Works

1. Text is tokenized into words

2. Each word is sent to the language detector

3. Detector returns language + confidence score

4. If confidence ≥ threshold and language is allowed:

   • An OverrideSpan is created with {"lang": "..."}

   • Short words (<3 chars) keep the default language

Performance

• Memory: ~100 MB for lingua models (loaded once)

• Speed: ~0.1-0.5 ms per word

• Accuracy: >90% for words with 5+ characters

Limitations

• Short words (<3 characters) use the default language only

• Proper nouns may be misdetected

• Requires lingua-language-detector installation

• Detection quality varies by word distinctiveness

Installation

pip install kokorog2p[mixed]

Language-Specific Number Handling

English

from kokorog2p.en.numbers import expand_number

print(expand_number("I have $42.50"))
# → I have forty-two dollars and fifty cents

German

from kokorog2p.de.numbers import expand_number

print(expand_number("Ich habe 42 Euro."))
# → Ich habe zweiundvierzig Euro.

French

from kokorog2p.fr.numbers import expand_number

print(expand_number("J'ai 42 euros."))
# → J'ai quarante-deux euros.

Fallback Languages

For languages not explicitly supported, kokorog2p falls back to espeak-ng:

from kokorog2p import get_g2p

# Spanish (uses espeak-ng)
g2p_es = get_g2p("es-es")

# Italian (uses espeak-ng)
g2p_it = get_g2p("it-it")

# Portuguese (uses espeak-ng)
g2p_pt = get_g2p("pt-br")

This provides basic support for 100+ languages via espeak-ng.

Next Steps

• See Advanced Usage for advanced usage patterns

• Check language-specific API docs:

  • English API

  • German API

  • French API

  • Czech API

  • Spanish API

  • Italian API

  • Portuguese API

  • Chinese API

  • Japanese API

  • Korean API

  • Hebrew API

  • Multilang Preprocessing