69 lines
2.5 KiB
Python
69 lines
2.5 KiB
Python
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import pynini
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from fun_text_processing.text_normalization.en.graph_utils import (
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DAMO_NOT_QUOTE,
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DAMO_SIGMA,
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GraphFst,
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delete_preserve_order,
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insert_space,
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)
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from pynini.lib import pynutil
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class FractionFst(GraphFst):
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"""
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Finite state transducer for verbalizing fraction
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e.g. fraction { integer: "drei" numerator: "eins" denominator: "zwei" }-> drei ein halb
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e.g. fraction { numerator: "vier" denominator: "zwei" } -> vier halbe
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e.g. fraction { numerator: "drei" denominator: "vier" } -> drei viertel
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Args:
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ordinal: ordinal GraphFst
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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, ordinal: GraphFst, deterministic: bool = True):
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super().__init__(name="fraction", kind="verbalize", deterministic=deterministic)
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optional_sign = pynini.closure(
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pynini.cross('negative: "true"', "minus ") + pynutil.delete(" "), 0, 1
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)
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change_one = pynini.cdrewrite(
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pynutil.add_weight(pynini.cross("eins", "ein"), weight=-0.0001),
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"[BOS]",
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"[EOS]",
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DAMO_SIGMA,
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)
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change_numerator_two = pynini.cdrewrite(
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pynini.cross("zweitel", "halbe"), "[BOS]", "[EOS]", DAMO_SIGMA
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)
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integer = pynutil.delete('integer_part: "') + change_one + pynutil.delete('" ')
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numerator = pynutil.delete('numerator: "') + change_one + pynutil.delete('" ')
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denominator = (
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pynutil.delete('denominator: "')
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+ pynini.closure(DAMO_NOT_QUOTE)
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@ (
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pynini.cdrewrite(
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pynini.closure(ordinal.ordinal_stem, 0, 1), "", "[EOS]", DAMO_SIGMA
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)
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+ pynutil.insert("tel")
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)
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@ change_numerator_two
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+ pynutil.delete('"')
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)
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integer += insert_space + pynini.closure(pynutil.insert("und ", weight=0.001), 0, 1)
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denominator_one_half = pynini.cdrewrite(
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pynini.cross("ein halbe", "ein halb"), "[BOS]", "[EOS]", DAMO_SIGMA
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)
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fraction_default = (numerator + insert_space + denominator) @ denominator_one_half
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self.graph = optional_sign + pynini.closure(integer, 0, 1) + fraction_default
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graph = self.graph + delete_preserve_order
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delete_tokens = self.delete_tokens(graph)
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self.fst = delete_tokens.optimize()
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