import pynini
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from fun_text_processing.inverse_text_normalization.fr.graph_utils import (
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DAMO_DIGIT,
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GraphFst,
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delete_extra_space,
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delete_space,
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)
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from fun_text_processing.inverse_text_normalization.fr.utils import get_abs_path
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from pynini.lib import pynutil
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|
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class TimeFst(GraphFst):
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"""
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Finite state transducer for verbalizing time, e.g.
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time { hours: "8" minutes: "30" suffix: "du matin"} -> 8 h 30
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time { hours: "8" minutes: "30" } -> 8 h 30
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time { hours: "8" minutes: "30" suffix: "du soir"} -> 20 h 30
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"""
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def __init__(self):
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super().__init__(name="time", kind="verbalize")
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hour_to_night = pynini.string_file(get_abs_path("data/time/hour_to_night.tsv"))
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day_suffixes = pynutil.delete('suffix: "am"')
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night_suffixes = pynutil.delete('suffix: "pm"')
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hour = (
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pynutil.delete("hours:")
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+ delete_space
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+ pynutil.delete('"')
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+ pynini.closure(DAMO_DIGIT, 1, 2)
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+ pynutil.delete('"')
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)
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minute = (
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pynutil.delete("minutes:")
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+ delete_extra_space
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+ pynutil.delete('"')
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+ pynini.closure(DAMO_DIGIT, 1, 2)
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+ pynutil.delete('"')
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)
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graph = (
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hour
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+ delete_extra_space
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+ pynutil.insert("h")
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+ minute.ques
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+ delete_space
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+ day_suffixes.ques
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)
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graph |= (
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hour @ hour_to_night
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+ delete_extra_space
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+ pynutil.insert("h")
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+ minute.ques
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+ delete_space
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+ night_suffixes
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)
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delete_tokens = self.delete_tokens(graph)
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self.fst = delete_tokens.optimize()
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