| """Canonical Bangla text normalizer = the paper's Stage-2 pipeline (single source of truth for |
| TTS input, CER reference, and training text). Order follows the paper: |
| 1. digit conversion (Latin 0-9 -> Bengali) [paper step 1] |
| 2. colon-numeral rewriting ("৪:৪৫" -> "৪ এর ৪৫") [paper step 2, from phonemizer.py] |
| 3. numeral-to-word expansion via bnnumerizer [paper step 3] -- applied PER NUMBER |
| (bnnumerizer mangles the 2nd+ number in a string; per-number application is a bug-fix) |
| 4. per-word Unicode normalization (bnunicodenormalizer) [paper step 4] |
| 5. honorific expansion (paper attribution_dict, 12) [paper step 5] |
| 6. whitespace collapse [paper step 6 = sentence seg + collapse] |
| Extensions beyond the paper (flagged, small): ordinals (৩য়->তৃতীয়), title abbreviations (ড./ডা./মো.), |
| thousands-comma stripping. The paper lists domain abbreviations as a known gap. |
| Use `for_tts(text)` before synthesis and `for_cer(text)` for reference/hypothesis before CER.""" |
| import re, unicodedata |
| from bnnumerizer import numerize |
| try: |
| from bnunicodenormalizer import Normalizer |
| _bnorm = Normalizer() |
| except Exception: |
| _bnorm = None |
|
|
| |
| HONORIFICS = { |
| "সাঃ": "সাল্লাল্লাহু আলাইহি ওয়া সাল্লাম", "রাঃ": "রাদিআল্লাহু আনহু", "রহঃ": "রাহিমাহুল্লাহ", |
| "হাঃ": "হাফিজাহুল্লাহ", "মাঃ": "মাদ্দাজিল্লুহু", "দাঃ বাঃ": "দামাত বারাকাতুহুম", |
| "আঃ": "আলাইহিস সালাম", "জিঃ": "জিল্লুল্লাহ", "কুঃ সিঃ": "কুদ্দিসা সিরুহু", |
| "আলঃ": "আলাইহিমুস সালাম", "রাযিঃ": "রাযিআল্লাহু আনহু", "মুহঃ": "মুহতারাম", |
| } |
| |
| ORDINALS = {"১ম":"প্রথম","২য়":"দ্বিতীয়","৩য়":"তৃতীয়","৪র্থ":"চতুর্থ","৫ম":"পঞ্চম","৬ষ্ঠ":"ষষ্ঠ","৭ম":"সপ্তম","৮ম":"অষ্টম","৯ম":"নবম","১০ম":"দশম"} |
| TITLES = {"ড.":"ডক্টর","ডা.":"ডাক্তার","মো.":"মোহাম্মদ","মোঃ":"মোহাম্মদ","প্রফ.":"প্রফেসর","ইঞ্জি.":"ইঞ্জিনিয়ার","অ্যাড.":"অ্যাডভোকেট"} |
| EN2BN = {"laptop":"ল্যাপটপ","monday":"মানডে","email":"ইমেইল","password":"পাসওয়ার্ড","software":"সফটওয়্যার", |
| "performance":"পারফরম্যান্স","team":"টিম","project":"প্রজেক্ট","online":"অনলাইন"} |
| _LAT2BN = str.maketrans("0123456789", "০১২৩৪৫৬৭৮৯") |
| _NUM = re.compile(r"[০-৯]+(?:[.][০-৯]+)*") |
| _COLON = re.compile(r"([০-৯]+):([০-৯]+)") |
|
|
| def _unicode_words(s): |
| if _bnorm is None: return s |
| out = [] |
| for w in s.split(): |
| try: r = _bnorm(w); out.append(r["normalized"] or w) |
| except Exception: out.append(w) |
| return " ".join(out) |
|
|
| def for_tts(text: str) -> str: |
| """Paper-order normalization producing the string the model should speak.""" |
| t = str(text) |
| for k, v in sorted(TITLES.items(), key=lambda kv: -len(kv[0])): t = t.replace(k, v) |
| t = t.translate(_LAT2BN) |
| t = _COLON.sub(lambda m: f"{m.group(1)} এর {m.group(2)}", t) |
| for k, v in sorted(ORDINALS.items(), key=lambda kv: -len(kv[0])): t = t.replace(k, v) |
| t = t.replace(",", "") |
| t = _NUM.sub(lambda m: numerize(m.group(0)), t) |
| t = _unicode_words(t) |
| for k, v in sorted(HONORIFICS.items(), key=lambda kv: -len(kv[0])): t = t.replace(k, _unicode_words(v)) |
| return re.sub(r"\s+", " ", t).strip() |
|
|
| def for_cer(text: str) -> str: |
| """Same expansions as for_tts, plus English->Bengali map, NFC, ZW strip, punctuation/space removal.""" |
| t = re.sub(r"[A-Za-z]+", lambda m: EN2BN.get(m.group(0).lower(), m.group(0)), str(text)) |
| t = for_tts(t) |
| t = unicodedata.normalize("NFC", t).replace("", "").replace("", "") |
| return re.sub(r"[।,\.!?;:\-—\s\"'‘’“”()]", "", t) |
|
|
| if __name__ == "__main__": |
| for s in ["নবী (সাঃ) বলেছেন","হযরত আলী (রাঃ) ও ইমাম আবু হানিফা (রহঃ)","সভা ৪:৪৫ এ শুরু","ড. ইউনূস ৩য় তলায় ১,২৫০ টাকা দিলেন","1966 সালে 400 টি বাঘ"]: |
| print(repr(s), "->", for_tts(s)) |
|
|
