import pynini
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from fun_text_processing.text_normalization.en.graph_utils import (
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DAMO_DIGIT,
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GraphFst,
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delete_space,
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insert_space,
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)
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from fun_text_processing.text_normalization.ru.alphabet import RU_ALPHA_OR_SPACE
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from pynini.lib import pynutil
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class TelephoneFst(GraphFst):
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"""
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Finite state transducer for classifying telephone, which includes country code, number part and extension
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E.g
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"8-913-983-56-01" -> telephone { number_part: "восемь девятьсот тринадцать девятьсот восемьдесят три пятьдесят шесть ноль один" }
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Args:
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number_names: number_names for cardinal and ordinal numbers
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deterministic: if True will provide a single transduction option,
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for False multiple transduction are generated (used for audio-based normalization)
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"""
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def __init__(self, number_names: dict, deterministic: bool = True):
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super().__init__(name="telephone", kind="classify", deterministic=deterministic)
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separator = pynini.cross("-", " ") # between components
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number = number_names["cardinal_names_nominative"]
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country_code = (
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pynutil.insert('country_code: "')
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+ pynini.closure(pynutil.add_weight(pynutil.delete("+"), 0.1), 0, 1)
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+ number
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+ separator
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+ pynutil.insert('"')
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)
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optional_country_code = pynini.closure(country_code + insert_space, 0, 1)
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number_part = (
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DAMO_DIGIT**3 @ number
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+ separator
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+ DAMO_DIGIT**3 @ number
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+ separator
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+ DAMO_DIGIT**2 @ number
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+ separator
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+ DAMO_DIGIT**2 @ (pynini.closure(pynini.cross("0", "ноль ")) + number)
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)
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number_part = pynutil.insert('number_part: "') + number_part + pynutil.insert('"')
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tagger_graph = (optional_country_code + number_part).optimize()
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# verbalizer
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verbalizer_graph = pynini.closure(
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pynutil.delete('country_code: "')
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+ pynini.closure(RU_ALPHA_OR_SPACE, 1)
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+ pynutil.delete('"')
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+ delete_space,
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0,
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1,
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)
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verbalizer_graph += (
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pynutil.delete('number_part: "')
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+ pynini.closure(RU_ALPHA_OR_SPACE, 1)
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+ pynutil.delete('"')
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)
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verbalizer_graph = verbalizer_graph.optimize()
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self.final_graph = (tagger_graph @ verbalizer_graph).optimize()
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self.fst = self.add_tokens(
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pynutil.insert('number_part: "') + self.final_graph + pynutil.insert('"')
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).optimize()
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