Add text normalization

leviticus/__init__.py

@@ -0,0 +1,125 @@
+"""
+text normalization functions
+"""
+
+from unidecode import unidecode
+import inflect
+import re
+
+_inflect = inflect.engine()
+_comma_number_re = re.compile(r'([0-9][0-9\,]+[0-9])')
+_decimal_number_re = re.compile(r'([0-9]+\.[0-9]+)')
+_pounds_re = re.compile(r'£([0-9\,]*[0-9]+)')
+_dollars_re = re.compile(r'\$([0-9\.\,]*[0-9]+)')
+_ordinal_re = re.compile(r'[0-9]+(st|nd|rd|th)')
+_number_re = re.compile(r'[0-9]+')
+
+# Regular expression matching whitespace:
+_whitespace_re = re.compile(r'\s+')
+
+# List of (regular expression, replacement) pairs for abbreviations:
+_abbreviations = [(re.compile('\\b%s\\.' % x[0], re.IGNORECASE), x[1]) for x in [
+    ('mrs', 'misess'),
+    ('mr', 'mister'),
+    ('dr', 'doctor'),
+    ('st', 'saint'),
+    ('co', 'company'),
+    ('jr', 'junior'),
+    ('maj', 'major'),
+    ('gen', 'general'),
+    ('drs', 'doctors'),
+    ('rev', 'reverend'),
+    ('lt', 'lieutenant'),
+    ('hon', 'honorable'),
+    ('sgt', 'sergeant'),
+    ('capt', 'captain'),
+    ('esq', 'esquire'),
+    ('ltd', 'limited'),
+    ('col', 'colonel'),
+    ('ft', 'fort'),
+]]
+
+
+def _remove_commas(m):
+    return m.group(1).replace(',', '')
+
+
+def _expand_decimal_point(m):
+    return m.group(1).replace('.', ' point ')
+
+
+def _expand_dollars(m):
+    match = m.group(1)
+    parts = match.split('.')
+    if len(parts) > 2:
+        return match + ' dollars'  # Unexpected format
+    dollars = int(parts[0]) if parts[0] else 0
+    cents = int(parts[1]) if len(parts) > 1 and parts[1] else 0
+    if dollars and cents:
+        dollar_unit = 'dollar' if dollars == 1 else 'dollars'
+        cent_unit = 'cent' if cents == 1 else 'cents'
+        return '%s %s, %s %s' % (dollars, dollar_unit, cents, cent_unit)
+    elif dollars:
+        dollar_unit = 'dollar' if dollars == 1 else 'dollars'
+        return '%s %s' % (dollars, dollar_unit)
+    elif cents:
+        cent_unit = 'cent' if cents == 1 else 'cents'
+        return '%s %s' % (cents, cent_unit)
+    else:
+        return 'zero dollars'
+
+
+def _expand_ordinal(m):
+    return _inflect.number_to_words(m.group(0))
+
+
+def _expand_number(m):
+    num = int(m.group(0))
+    if num > 1000 and num < 3000:
+        if num == 2000:
+            return 'two thousand'
+        elif num > 2000 and num < 2010:
+            return 'two thousand ' + _inflect.number_to_words(num % 100)
+        elif num % 100 == 0:
+            return _inflect.number_to_words(num // 100) + ' hundred'
+        else:
+            return _inflect.number_to_words(num, andword='', zero='oh', group=2).replace(', ', ' ')
+    else:
+        return _inflect.number_to_words(num, andword='')
+
+
+def normalize_numbers(text):
+    text = re.sub(_comma_number_re, _remove_commas, text)
+    text = re.sub(_pounds_re, r'\1 pounds', text)
+    text = re.sub(_dollars_re, _expand_dollars, text)
+    text = re.sub(_decimal_number_re, _expand_decimal_point, text)
+    text = re.sub(_ordinal_re, _expand_ordinal, text)
+    text = re.sub(_number_re, _expand_number, text)
+    return text
+
+
+def expand_abbreviations(text):
+    for regex, replacement in _abbreviations:
+        text = re.sub(regex, replacement, text)
+    return text
+
+
+def expand_numbers(text):
+    return normalize_numbers(text)
+
+
+def collapse_whitespace(text):
+    return re.sub(_whitespace_re, ' ', text)
+
+
+def convert_to_ascii(text):
+    return unidecode(text)
+
+
+def normalize(text):
+    text = convert_to_ascii(text)
+    text = text.lower()
+    text = expand_numbers(text)
+    text = expand_abbreviations(text)
+    text = collapse_whitespace(text)
+    return text

requirements.txt

@@ -1,6 +1,7 @@
 absl-py==2.0.0
 aiohttp==3.8.5
 aiosignal==1.3.1
+annotated-types==0.6.0
 appnope==0.1.3
 asttokens==2.4.0
 astunparse==1.6.3
@@ -36,6 +37,7 @@ h5py==3.9.0
 huggingface-hub==0.17.3
 idna==3.4
 importlib-metadata==6.8.0
+inflect==7.0.0
 ipykernel==6.25.2
 ipython==8.16.1
 jedi==0.19.1
@@ -79,6 +81,8 @@ pyarrow==13.0.0
 pyasn1==0.5.0
 pyasn1-modules==0.3.0
 pycparser==2.21
+pydantic==2.4.2
+pydantic_core==2.10.1
 Pygments==2.16.1
 python-dateutil==2.8.2
 pytz==2023.3.post1
@@ -113,6 +117,7 @@ traitlets==5.11.2
 transformers==4.34.0
 typing_extensions==4.8.0
 tzdata==2023.3
+Unidecode==1.3.7
 urllib3==1.26.17
 wcwidth==0.2.8
 Werkzeug==3.0.0

scripts/prep_push_to_hf.py

@@ -7,6 +7,8 @@ import numpy as np
 import pandas as pd
 from datasets import Audio, Dataset, DatasetDict
 
+from leviticus import normalize
+
 MAX_DURATION_IN_SECONDS = 10.0
 MIN_DURATION_IN_SECONDS = 1.0
 MAX_LEN = 50
@@ -40,6 +42,7 @@ data = {
     "audio": wavs,
     "file": [basename(w) for w in wavs],
     "text": metadata[1],
+    "norm": metadata[1].map(lambda x: normalize(x)),
     "duration": [librosa.get_duration(path=w) for w in wavs],
 }