Urdu TTS G2P support to NeMo

[mwzkhalil]

[Feature/PR] Add Urdu (ur-PK) IPA G2P support to NeMo TTS

#15445

Module: nemo/collections/tts/g2p/
Type: New language support

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Summary

This PR adds UrduIpaG2p — a Grapheme-to-Phoneme module for Urdu (ur-PK)
that converts Urdu text written in Nastaliq/Naskh script into IPA phoneme
sequences. It follows the exact same design pattern as the existing
EnglishG2p (en_us_arpabet.py) and ChineseG2p (zh_cn_pinyin.py)
modules, subclassing BaseG2p directly.

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Motivation

Urdu is spoken by approximately 230 million people worldwide and is the
national language of Pakistan. Despite this, NeMo currently has no G2P support
for Urdu, making it impossible to train TTS models for Urdu using the standard
NeMo pipeline.

This contribution provides:

• A complete, tested UrduIpaG2p class (nemo/collections/tts/g2p/models/ur_pk_ipa.py)
• A pronunciation dictionary of ~470,000 Urdu word/phrase → IPA entries in JSON format
• Full feature parity with existing NeMo G2P modules

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Urdu Script Notes

Property	Detail
Script	Nastaliq / Naskh (Arabic-based, RTL)
Unicode range	U+0600–U+06FF (core), U+0750–U+077F (extensions: ڈ ڑ ھ ے ں)
Letter case	None — no uppercase/lowercase distinction
Phoneme set	IPA (Urdu-specific phones: ɦ, ʔ, ɖ, ɽ, t̪, d̪, etc.)
Word boundary	Whitespace-delimited (after NFC normalisation)

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Files Changed

nemo/collections/tts/g2p/models/ur_pk_ipa.py     ← new file
nemo/collections/tts/g2p/modules.py               ← add UrduIpaG2p import
scripts/tts_dataset_files/urdu_ipa_dict.json      ← ~470k entries
tests/collections/tts/g2p/test_ur_pk_ipa.py       ← new tests

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Implementation Details

Dictionary format (JSON):

{
  "غیر حاضری":    "ɣɛːr hɑːzriː",
  "شوکت خانم ليب": "ʃoːˈkət̪ xɑːˈnəm leːb",
  "مختار احمد":   "mʊxˈt̪aːr ˈæhməd"
}

Keys are single words or multi-word phrases; values are space-separated IPA.

Key design decisions:

1. Subclasses BaseG2p directly (not IpaG2p) — IpaG2p.__init__
   unconditionally calls set_grapheme_case(), which is meaningless for
   Urdu script (no letter case) and raises ValueError with case=None.
   This mirrors the approach taken by EnglishG2p and ChineseG2p.

2. Longest-phrase-first matching — __call__ tries up to max_phrase_len
   (default 4) consecutive tokens as a phrase key before falling back to
   single-word lookup, enabling correct handling of named entities and
   compound words that span multiple tokens.

3. NFC normalisation — both input text and dictionary keys are
   NFC-normalised at load and inference time, ensuring consistent lookup
   regardless of how the Urdu text was composed.

4. Full feature parity with existing G2P modules:

   • heteronyms support
   • apply_to_oov_word fallback
   • use_stresses toggle
   • phoneme_probability for mixed grapheme/phoneme training
   • Hyphenated OOV word splitting

Usage:

from nemo.collections.tts.g2p.models.ur_pk_ipa import UrduIpaG2p

g2p = UrduIpaG2p(phoneme_dict="scripts/tts_dataset_files/urdu_ipa_dict.json")

g2p("غیر حاضری")
# -> ['ɣɛːr', 'hɑːzriː']

g2p("شوکت خانم ليب")
# -> ['ʃoːˈkət̪', 'xɑːˈnəm', 'leːb']

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Pronunciation Dictionary

• Size: ~470,000 entries
• Coverage: single words, named entities, multi-word phrases, abbreviations
• Source: Collected and IPA-transcribed for Urdu TTS research
• Format: UTF-8 JSON, NFC-normalised

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Testing

python3 -m pytest tests/collections/tts/g2p/test_ur_pk_ipa.py -v

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Checklist

• Follows existing NeMo G2P module patterns (EnglishG2p, ChineseG2p)
• Subclasses BaseG2p directly
• Full docstrings (module, class, all methods)
• Registered in modules.py
• ~470k entry pronunciation dictionary included
• Unit tests
• Config YAML example (happy to add if requested)
• Integration with IPATokenizer for FastPitch/VITS training

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Related Issues / References

• Urdu phonology: https://en.wikipedia.org/wiki/Urdu_phonology
• Unicode Arabic block: https://www.unicode.org/charts/PDF/U0600.pdf
• eSpeak-NG Urdu support: https://github.com/espeak-ng/espeak-ng

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I am happy to address review feedback, add a YAML config example, or extend
the dictionary coverage. Thank you for considering this contribution!