src/transformers/models/whisper/english_normalizer.py/EnglishNumberNormalizer/postprocess
class EnglishNumberNormalizer:    def postprocess(self, s: str):
        def combine_cents(m: Match):
            try:
                currency = m.group(1)
                integer = m.group(2)
                cents = int(m.group(3))
                return f"{currency}{integer}.{cents:02d}"
            except ValueError:
                return m.string

        def extract_cents(m: Match):
            try:
                return f"¢{int(m.group(1))}"
            except ValueError:
                return m.string

        # apply currency postprocessing; "$2 and ¢7" -> "$2.07"
        s = re.sub(r"([€£$])([0-9]+) (?:and )?¢([0-9]{1,2})\b", combine_cents, s)
        s = re.sub(r"[€£$]0.([0-9]{1,2})\b", extract_cents, s)

        # write "one(s)" instead of "1(s)", just for the readability
        s = re.sub(r"\b1(s?)\b", r"one\1", s)

        return s