404 lines
15 KiB
Python
404 lines
15 KiB
Python
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"""Text preprocessing utilities for the Voxtral TTS demo.
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Provides text normalization and cleanup before sending input to the TTS model,
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including:
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- Removal of invisible Unicode characters (zero-width spaces, bidi marks, etc.)
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- Flattening of Markdown and HTML formatting
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- Verbalization of numbers and currency ($1.50 -> "one dollar and fifty cents")
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- Normalization of punctuation and dashes
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- Insertion of terminal punctuation when missing
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"""
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import re
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from html import unescape
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# Invisible Unicode chars often introduced by copy/paste.
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_INVISIBLE_UNICODE_RE = re.compile(
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"["
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"\u200b" # zero-width space
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"\u200e-\u200f" # bidi marks
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"\u2028-\u2029" # line/paragraph separators
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"\u2060-\u2064" # word joiner, invisible math operators
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"\u00ad" # soft hyphen
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"\u180e" # mongolian vowel separator
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"\ufeff" # BOM / zero-width no-break space
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"\ufff9-\ufffb" # interlinear annotations
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"]"
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)
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# Keeps U+200C (ZWNJ) and U+200D (ZWJ).
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_LINE_BREAK_RE = re.compile(r"(?:\r\n|\r|\n)+")
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_REPEATED_PUNCT_RE = re.compile(r"([!?])\1+")
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_ASCII_ELLIPSIS_RUN_RE = re.compile(r"\.{3,}")
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_UNICODE_HYPHEN_TO_ASCII_RE = re.compile("[\u2010\u2011]")
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_DASH_LIKE_CHARS = "\u002d\u2013\u2212"
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_DASH_LIKE_CLASS = re.escape(_DASH_LIKE_CHARS)
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_CURRENCY_CHARS = "$€£¥₹¢"
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_MULTI_HYPHEN_RE = re.compile(rf"[{_DASH_LIKE_CLASS}]{{2,}}")
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_STANDALONE_HYPHEN_RE = re.compile(rf"(?<=\s)[{_DASH_LIKE_CLASS}](?=\s)")
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_TERMINAL_PUNCT = ".!?\u2026\u061f\u3002\uff01\uff1f"
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_PARENTHETICAL_RE = re.compile(r"\s*\(([^()]+)\)\s*")
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_SIMPLE_NUMERIC_PAREN_CONTENT_RE = re.compile(r"^\s*[$€£¥₹¢]?\s*[+\-−–]?\d+(?:[.,]\d+)?\s*%?\s*$")
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_MD_FENCE_RE = re.compile(r"```[\s\S]*?```|~~~[\s\S]*?~~~")
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_MD_IMAGE_LINK_RE = re.compile(r"!\[([^\]]*)\]\(([^)]*)\)")
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_MD_LINK_RE = re.compile(r"\[([^\]]+)\]\(([^)]*)\)")
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_MD_INLINE_CODE_RE = re.compile(r"`([^`]+)`")
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_MD_HEADING_RE = re.compile(r"^\s{0,3}#{1,6}\s*", re.MULTILINE)
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_MD_UNORDERED_RE = re.compile(r"^\s*[-*+]\s+", re.MULTILINE)
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_MD_ORDERED_RE = re.compile(r"^\s*\d{1,4}[.)]\s+", re.MULTILINE)
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_MD_BLOCKQUOTE_RE = re.compile(r"^\s{0,3}>\s?", re.MULTILINE)
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_MD_BR_TAG_RE = re.compile(r"(?i)<br\s*/?>")
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_MD_HTML_TAG_RE = re.compile(r"</?[a-zA-Z][^>]*>")
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_MD_AUTOLINK_RE = re.compile(r"<https?://[^>]+>")
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_MD_URL_RE = re.compile(r"https?://\S+")
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_ONES = {
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0: "zero",
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1: "one",
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2: "two",
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3: "three",
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4: "four",
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5: "five",
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6: "six",
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7: "seven",
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8: "eight",
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9: "nine",
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}
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_TEENS = {
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10: "ten",
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11: "eleven",
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12: "twelve",
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13: "thirteen",
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14: "fourteen",
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15: "fifteen",
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16: "sixteen",
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17: "seventeen",
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18: "eighteen",
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19: "nineteen",
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}
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_TENS = {
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20: "twenty",
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30: "thirty",
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40: "forty",
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50: "fifty",
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60: "sixty",
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70: "seventy",
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80: "eighty",
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90: "ninety",
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}
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_SCALES = ["", "thousand", "million", "billion", "trillion", "quadrillion"]
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_TOKEN_RE = re.compile(
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r"""
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(?P<currency>
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(?P<symbol>[$£€¥₹¢])
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(?P<amount>\d[\d,]*(?:\.\d+)?)
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)
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(?P<number>
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(?<!\w)-?\d[\d,]*(?:\.\d+)?\b
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)
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""",
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re.VERBOSE,
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)
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_CURRENCY_INFO = {
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"$": ("dollar", "dollars", "cent", "cents"),
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"£": ("pound", "pounds", "penny", "pence"),
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"€": ("euro", "euros", "cent", "cents"),
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"¥": ("yen", "yen", None, None),
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"₹": ("rupee", "rupees", "paise", "paise"),
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"¢": ("cent", "cents", None, None),
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}
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def _flatten_markdown_for_tts(text: str) -> str:
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text = _MD_FENCE_RE.sub(" Code example omitted. ", text)
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text = unescape(text)
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text = _MD_BR_TAG_RE.sub(" ", text)
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text = _MD_IMAGE_LINK_RE.sub(lambda match: match.group(1).strip() or "image", text)
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text = _MD_LINK_RE.sub(lambda match: match.group(1), text)
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text = _MD_AUTOLINK_RE.sub("link", text)
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text = _MD_URL_RE.sub("link", text)
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text = _MD_INLINE_CODE_RE.sub(lambda match: match.group(1), text)
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text = _MD_HEADING_RE.sub("", text)
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text = _MD_UNORDERED_RE.sub("", text)
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text = _MD_ORDERED_RE.sub("", text)
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text = _MD_BLOCKQUOTE_RE.sub("", text)
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text = _MD_HTML_TAG_RE.sub(" ", text)
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return text
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def _next_non_space_char(text: str, start_index: int) -> str | None:
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index = start_index
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while index < len(text) and text[index].isspace():
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index += 1
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if index >= len(text):
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return None
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return text[index]
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def _replace_standalone_hyphens(text: str) -> str:
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def replace(match: re.Match[str]) -> str:
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next_char = _next_non_space_char(text, match.end())
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if next_char is None:
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return match.group(0)
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if next_char.isdigit() or next_char in _CURRENCY_CHARS:
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return match.group(0)
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return "\u2014"
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return _STANDALONE_HYPHEN_RE.sub(replace, text)
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def _replace_textual_parentheticals(text: str) -> str:
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def normalize_parenthetical(inner: str) -> str:
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normalized = inner
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normalized = re.sub(r"(?i)\bN\s*/\s*A\b", "not available", normalized)
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normalized = re.sub(r"\s*(?:\+/-|±)\s*", " plus or minus ", normalized)
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normalized = re.sub(r"\s*>=\s*", " greater than or equal to ", normalized)
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normalized = re.sub(r"\s*<=\s*", " less than or equal to ", normalized)
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normalized = re.sub(r"\s*>\s*", " greater than ", normalized)
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normalized = re.sub(r"\s*<\s*", " less than ", normalized)
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normalized = re.sub(r"\s*~\s*", " about ", normalized)
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normalized = re.sub(r"#\s*(\d+)\b", r"number \1", normalized)
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normalized = re.sub(r"(\d+(?:\.\d+)?)\s*ms\b", r"\1 milliseconds", normalized, flags=re.IGNORECASE)
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normalized = re.sub(r"(\d+(?:\.\d+)?)\s*h\b", r"\1 hours", normalized, flags=re.IGNORECASE)
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normalized = re.sub(r"(\d+(?:\.\d+)?)\s*%", r"\1 percent", normalized)
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normalized = re.sub(r"\s*\+\s*", " plus ", normalized)
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normalized = re.sub(r"\s*=\s*", " equals ", normalized)
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normalized = re.sub(r"\s+", " ", normalized).strip()
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return normalized
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def replace(match: re.Match[str]) -> str:
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inner = match.group(1).strip()
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if not inner:
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return match.group(0)
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if _SIMPLE_NUMERIC_PAREN_CONTENT_RE.fullmatch(inner):
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return match.group(0)
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normalized = normalize_parenthetical(inner)
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return f"\u2014{normalized}\u2014"
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return _PARENTHETICAL_RE.sub(replace, text)
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def _verbalize_sub_thousand(n: int, *, use_and: bool = False) -> str:
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if not 0 <= n <= 999:
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raise ValueError(f"Expected sub-thousand integer in [0, 999], got {n=}")
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parts: list[str] = []
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hundreds = n // 100
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rem = n % 100
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if hundreds:
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parts.append(f"{_ONES[hundreds]} hundred")
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if rem and use_and:
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parts.append("and")
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if rem:
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if rem < 10:
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parts.append(_ONES[rem])
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elif rem < 20:
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parts.append(_TEENS[rem])
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else:
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tens = (rem // 10) * 10
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ones = rem % 10
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if ones:
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parts.append(f"{_TENS[tens]}-{_ONES[ones]}")
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else:
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parts.append(_TENS[tens])
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return " ".join(parts) if parts else "zero"
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def _verbalize_integer_en(num_str: str, *, use_and: bool = False) -> str:
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s = num_str.replace(",", "").strip()
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if not re.fullmatch(r"\d+", s):
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raise ValueError(f"Not a plain integer: {num_str}")
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n = int(s)
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if n == 0:
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return "zero"
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groups: list[int] = []
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while n > 0:
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groups.append(n % 1000)
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n //= 1000
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if len(groups) > len(_SCALES):
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raise ValueError(f"Integer magnitude too large to verbalize safely: {num_str}")
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parts: list[str] = []
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for scale_idx in range(len(groups) - 1, -1, -1):
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group_val = groups[scale_idx]
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if group_val == 0:
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continue
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group_words = _verbalize_sub_thousand(
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group_val,
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use_and=use_and and scale_idx == 0 and len(groups) > 1,
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)
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scale_word = _SCALES[scale_idx]
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parts.append(f"{group_words} {scale_word}".strip())
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return " ".join(parts)
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def _verbalize_decimal_en(num_str: str, *, use_and: bool = False) -> str:
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s = num_str.replace(",", "").strip()
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match = re.fullmatch(r"(\d+)\.(\d+)", s)
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if not match:
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raise ValueError(f"Not a plain decimal: {num_str}")
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int_part, frac_part = match.groups()
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int_words = _verbalize_integer_en(int_part, use_and=use_and)
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frac_words = "-".join(_ONES[int(ch)] for ch in frac_part)
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return f"{int_words} point {frac_words}"
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def _verbalize_number_en(num_str: str, *, use_and: bool = False) -> str:
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s = num_str.strip()
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if s.startswith("-"):
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inner = s[1:]
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if not inner:
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raise ValueError(f"Unsupported numeric format: {num_str}")
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return f"negative {_verbalize_number_en(inner, use_and=use_and)}"
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if re.fullmatch(r"\d{4}", s):
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year = int(s)
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if 1400 <= year < 2100:
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if year == 2000:
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return "two thousand"
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first_two = year // 100
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last_two = year % 100
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if 1400 <= year <= 1999:
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if last_two == 0:
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return f"{_verbalize_integer_en(str(first_two), use_and=use_and)} hundred"
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return f"{_verbalize_integer_en(str(first_two), use_and=use_and)} {_verbalize_sub_thousand(last_two)}"
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if 2001 <= year <= 2009:
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return f"two thousand {_ONES[last_two]}"
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if 2010 <= year <= 2099:
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return f"twenty {_verbalize_sub_thousand(last_two)}"
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if re.fullmatch(r"\d[\d,]*", s):
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return _verbalize_integer_en(s, use_and=use_and)
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if re.fullmatch(r"\d[\d,]*\.\d+", s):
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return _verbalize_decimal_en(s, use_and=use_and)
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raise ValueError(f"Unsupported numeric format: {num_str}")
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def _parse_currency_token(token: str) -> tuple[str, int, str | None]:
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match = re.fullmatch(r"([$£€¥₹¢])(\d[\d,]*)(?:\.(\d+))?", token.strip())
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if not match:
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raise ValueError(f"Not a supported currency amount: {token}")
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symbol, whole_part, frac_part = match.groups()
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whole = int(whole_part.replace(",", ""))
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return symbol, whole, frac_part
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def _verbalize_currency_decimal_en(symbol: str, whole: int, frac_part: str) -> str:
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singular_major, plural_major, _, _ = _CURRENCY_INFO[symbol]
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major_unit = singular_major if whole == 1 else plural_major
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whole_words = _verbalize_integer_en(str(whole), use_and=False)
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frac_words = "-".join(_ONES[int(ch)] for ch in frac_part)
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return f"{whole_words} point {frac_words} {major_unit}"
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def _verbalize_currency_en(token: str, *, use_and: bool = True, short: bool = False) -> str:
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symbol, whole, frac_part = _parse_currency_token(token)
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singular_major, plural_major, singular_minor, plural_minor = _CURRENCY_INFO[symbol]
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if short and symbol != "$":
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short = False
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if frac_part is not None and len(frac_part) > 2:
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return _verbalize_currency_decimal_en(symbol, whole, frac_part)
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minor = None
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if frac_part is not None:
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frac_2 = (frac_part + "00")[:2]
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minor = int(frac_2)
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if not short:
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whole_words = _verbalize_integer_en(str(whole), use_and=use_and)
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major_unit = singular_major if whole == 1 else plural_major
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if symbol in {"¥", "¢"}:
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if frac_part is None or set(frac_part) == {"0"}:
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return f"{whole_words} {major_unit}"
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return _verbalize_currency_decimal_en(symbol, whole, frac_part)
|
||
|
|
if minor is None or minor == 0:
|
||
|
|
return f"{whole_words} {major_unit}"
|
||
|
|
if whole == 0:
|
||
|
|
minor_words = _verbalize_integer_en(str(minor), use_and=False)
|
||
|
|
minor_unit = singular_minor if minor == 1 else plural_minor
|
||
|
|
return f"{minor_words} {minor_unit}"
|
||
|
|
minor_words = _verbalize_integer_en(str(minor), use_and=False)
|
||
|
|
minor_unit = singular_minor if minor == 1 else plural_minor
|
||
|
|
return f"{whole_words} {major_unit} and {minor_words} {minor_unit}"
|
||
|
|
|
||
|
|
if minor is None or minor == 0:
|
||
|
|
whole_words = _verbalize_integer_en(str(whole), use_and=False)
|
||
|
|
major_unit = singular_major if whole == 1 else plural_major
|
||
|
|
return f"{whole_words} {major_unit}"
|
||
|
|
if whole == 0:
|
||
|
|
minor_words = _verbalize_integer_en(str(minor), use_and=False)
|
||
|
|
minor_unit = singular_minor if minor == 1 else plural_minor
|
||
|
|
return f"{minor_words} {minor_unit}"
|
||
|
|
if 0 <= minor <= 9:
|
||
|
|
return f"{_verbalize_integer_en(str(whole), use_and=False)} oh {_ONES[minor]}"
|
||
|
|
return f"{_verbalize_integer_en(str(whole), use_and=False)} {_verbalize_integer_en(str(minor), use_and=False)}"
|
||
|
|
|
||
|
|
|
||
|
|
def _should_verbalize_plain_number(token: str) -> bool:
|
||
|
|
s = token.strip()
|
||
|
|
if s.startswith("-"):
|
||
|
|
s = s[1:]
|
||
|
|
raw_int_part = s.split(".", 1)[0]
|
||
|
|
int_no_commas = raw_int_part.replace(",", "")
|
||
|
|
if not re.fullmatch(r"\d+", int_no_commas):
|
||
|
|
return False
|
||
|
|
value = int(int_no_commas)
|
||
|
|
# Only rewrite large comma-separated values (e.g. 1,234,567).
|
||
|
|
return 1_000_000 <= value < 1e18 and "," in raw_int_part
|
||
|
|
|
||
|
|
|
||
|
|
def _auto_verbalize_safe_numbers_in_text(text: str) -> str:
|
||
|
|
matches = list(_TOKEN_RE.finditer(text))
|
||
|
|
currency_symbols = [m.group("symbol") for m in matches if m.group("currency") is not None]
|
||
|
|
only_dollar_repetitions = currency_symbols and set(currency_symbols) == {"$"} and len(currency_symbols) > 1
|
||
|
|
first_dollar_done = False
|
||
|
|
|
||
|
|
def repl(match: re.Match[str]) -> str:
|
||
|
|
nonlocal first_dollar_done
|
||
|
|
if match.group("currency") is not None:
|
||
|
|
token = match.group("currency")
|
||
|
|
symbol = match.group("symbol")
|
||
|
|
try:
|
||
|
|
short = False
|
||
|
|
if only_dollar_repetitions and symbol == "$":
|
||
|
|
if first_dollar_done:
|
||
|
|
short = True
|
||
|
|
else:
|
||
|
|
first_dollar_done = True
|
||
|
|
return _verbalize_currency_en(token, use_and=True, short=short)
|
||
|
|
except (ValueError, IndexError):
|
||
|
|
return token
|
||
|
|
token = match.group("number")
|
||
|
|
try:
|
||
|
|
if not _should_verbalize_plain_number(token):
|
||
|
|
return token
|
||
|
|
return _verbalize_number_en(token, use_and=True)
|
||
|
|
except (ValueError, IndexError):
|
||
|
|
return token
|
||
|
|
|
||
|
|
return _TOKEN_RE.sub(repl, text)
|
||
|
|
|
||
|
|
|
||
|
|
def sanitize_tts_input_text_for_demo(text: str) -> str:
|
||
|
|
"""Normalize text before sending it to TTS."""
|
||
|
|
raw_text = text
|
||
|
|
text = _flatten_markdown_for_tts(text)
|
||
|
|
text = _INVISIBLE_UNICODE_RE.sub("", text)
|
||
|
|
text = _LINE_BREAK_RE.sub(" ", text)
|
||
|
|
text = _auto_verbalize_safe_numbers_in_text(text)
|
||
|
|
text = _replace_textual_parentheticals(text)
|
||
|
|
text = _UNICODE_HYPHEN_TO_ASCII_RE.sub("-", text)
|
||
|
|
text = _ASCII_ELLIPSIS_RUN_RE.sub("...", text)
|
||
|
|
text = _REPEATED_PUNCT_RE.sub(r"\1", text)
|
||
|
|
text = _MULTI_HYPHEN_RE.sub("\u2014", text)
|
||
|
|
text = _replace_standalone_hyphens(text)
|
||
|
|
text = re.sub(r"\s+", " ", text).strip()
|
||
|
|
if text and text[-1] not in _TERMINAL_PUNCT:
|
||
|
|
text += "."
|
||
|
|
if not text:
|
||
|
|
raise ValueError(f"Speech input is empty after sanitization, got {raw_text=}")
|
||
|
|
return text
|