First draft of Korean Cardinal ITN

nemo_text_processing/inverse_text_normalization/inverse_normalize.py

@@ -131,6 +131,11 @@ def __init__(
             from nemo_text_processing.inverse_text_normalization.ja.verbalizers.verbalize_final import (
                 VerbalizeFinalFst,
             )
+        elif lang == 'ko':  # Korean
+            from nemo_text_processing.inverse_text_normalization.ko.taggers.tokenize_and_classify import ClassifyFst
+            from nemo_text_processing.inverse_text_normalization.ko.verbalizers.verbalize_final import (
+                VerbalizeFinalFst,
+            )
 
         self.tagger = ClassifyFst(
             cache_dir=cache_dir, whitelist=whitelist, overwrite_cache=overwrite_cache, input_case=input_case
@@ -175,7 +180,7 @@ def parse_args():
     parser.add_argument(
         "--language",
         help="language",
-        choices=['en', 'de', 'es', 'pt', 'ru', 'fr', 'sv', 'vi', 'ar', 'es_en', 'zh', 'hi', 'hy', 'mr', 'ja'],
+        choices=['en', 'de', 'es', 'pt', 'ru', 'fr', 'sv', 'vi', 'ar', 'es_en', 'zh', 'hi', 'hy', 'mr', 'ja', 'ko'],
         default="en",
         type=str,
     )

nemo_text_processing/inverse_text_normalization/ko/__init__.py

@@ -0,0 +1,17 @@
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from nemo_text_processing.inverse_text_normalization.ko.taggers.tokenize_and_classify import ClassifyFst
+from nemo_text_processing.inverse_text_normalization.ko.verbalizers.verbalize import VerbalizeFst
+from nemo_text_processing.inverse_text_normalization.ko.verbalizers.verbalize_final import VerbalizeFinalFst

nemo_text_processing/inverse_text_normalization/ko/data/__init__.py

@@ -0,0 +1,13 @@
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

nemo_text_processing/inverse_text_normalization/ko/data/numbers/__init__.py

@@ -0,0 +1,13 @@
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.

nemo_text_processing/inverse_text_normalization/ko/data/numbers/digit.tsv

@@ -0,0 +1,9 @@
+일	1
+이	2
+삼	3
+사	4
+오	5
+육	6
+칠	7
+팔	8
+구	9

nemo_text_processing/inverse_text_normalization/ko/data/numbers/thousands.tsv

@@ -0,0 +1,11 @@
+억
+조
+경
+해
+자
+양
+구
+간
+정
+재
+극

nemo_text_processing/inverse_text_normalization/ko/graph_utils.py

@@ -0,0 +1,292 @@
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+# Copyright 2015 and onwards Google, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import logging
+import os
+import string
+from pathlib import Path
+from typing import Dict
+
+import pynini
+from pynini import Far
+from pynini.examples import plurals
+from pynini.export import export
+from pynini.lib import byte, pynutil, utf8
+
+from nemo_text_processing.text_normalization.en.utils import get_abs_path, load_labels
+
+NEMO_CHAR = utf8.VALID_UTF8_CHAR
+
+NEMO_NARROW_NON_BREAK_SPACE = "\u202f"
+NEMO_DIGIT = byte.DIGIT
+NEMO_LOWER = pynini.union(*string.ascii_lowercase).optimize()
+NEMO_UPPER = pynini.union(*string.ascii_uppercase).optimize()
+NEMO_ALPHA = pynini.union(NEMO_LOWER, NEMO_UPPER).optimize()
+NEMO_ALNUM = pynini.union(NEMO_DIGIT, NEMO_ALPHA).optimize()
+NEMO_HEX = pynini.union(*string.hexdigits).optimize()
+NEMO_NON_BREAKING_SPACE = "\u00a0"
+NEMO_SPACE = " "
+NEMO_WHITE_SPACE = pynini.union(" ", "\t", "\n", "\r", u"\u00a0").optimize()
+NEMO_NOT_SPACE = pynini.difference(NEMO_CHAR, NEMO_WHITE_SPACE).optimize()
+NEMO_NOT_QUOTE = pynini.difference(NEMO_CHAR, r'"').optimize()
+
+NEMO_PUNCT = pynini.union(*map(pynini.escape, string.punctuation)).optimize()
+NEMO_GRAPH = pynini.union(NEMO_ALNUM, NEMO_PUNCT).optimize()
+
+NEMO_SIGMA = pynini.closure(NEMO_CHAR)
+
+NEMO_NOT_ALPHA = pynini.difference(NEMO_SIGMA, NEMO_ALPHA).optimize()
+NEMO_LOWER_NOT_A = pynini.union(
+    "b",
+    "c",
+    "d",
+    "e",
+    "f",
+    "g",
+    "h",
+    "i",
+    "j",
+    "k",
+    "l",
+    "m",
+    "n",
+    "o",
+    "p",
+    "q",
+    "r",
+    "s",
+    "t",
+    "u",
+    "v",
+    "w",
+    "x",
+    "y",
+    "z",
+).optimize()
+
+delete_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE))
+delete_zero_or_one_space = pynutil.delete(pynini.closure(NEMO_WHITE_SPACE, 0, 1))
+insert_space = pynutil.insert(" ")
+delete_extra_space = pynini.cross(pynini.closure(NEMO_WHITE_SPACE, 1), " ")
+delete_preserve_order = pynini.closure(
+    pynutil.delete(" preserve_order: true")
+    | (pynutil.delete(" field_order: \"") + NEMO_NOT_QUOTE + pynutil.delete("\""))
+)
+
+suppletive = pynini.string_file(get_abs_path("data/suppletive.tsv"))
+# _v = pynini.union("a", "e", "i", "o", "u")
+_c = pynini.union(
+    "b", "c", "d", "f", "g", "h", "j", "k", "l", "m", "n", "p", "q", "r", "s", "t", "v", "w", "x", "y", "z"
+)
+_ies = NEMO_SIGMA + _c + pynini.cross("y", "ies")
+_es = NEMO_SIGMA + pynini.union("s", "sh", "ch", "x", "z") + pynutil.insert("es")
+_s = NEMO_SIGMA + pynutil.insert("s")
+
+graph_plural = plurals._priority_union(
+    suppletive, plurals._priority_union(_ies, plurals._priority_union(_es, _s, NEMO_SIGMA), NEMO_SIGMA), NEMO_SIGMA
+).optimize()
+
+SINGULAR_TO_PLURAL = graph_plural
+PLURAL_TO_SINGULAR = pynini.invert(graph_plural)
+TO_LOWER = pynini.union(*[pynini.cross(x, y) for x, y in zip(string.ascii_uppercase, string.ascii_lowercase)])
+TO_UPPER = pynini.invert(TO_LOWER)
+MIN_NEG_WEIGHT = -0.0001
+MIN_POS_WEIGHT = 0.0001
+INPUT_CASED = "cased"
+INPUT_LOWER_CASED = "lower_cased"
+MINUS = pynini.union("minus", "Minus").optimize()
+
+
+def capitalized_input_graph(
+    graph: 'pynini.FstLike', original_graph_weight: float = None, capitalized_graph_weight: float = None
+) -> 'pynini.FstLike':
+    """
+    Allow graph input to be capitalized, e.g. for ITN)
+
+    Args:
+        graph: FstGraph
+        original_graph_weight: weight to add to the original `graph`
+        capitalized_graph_weight: weight to add to the capitalized graph
+    """
+    capitalized_graph = pynini.compose(TO_LOWER + NEMO_SIGMA, graph).optimize()
+
+    if original_graph_weight is not None:
+        graph = pynutil.add_weight(graph, weight=original_graph_weight)
+
+    if capitalized_graph_weight is not None:
+        capitalized_graph = pynutil.add_weight(capitalized_graph, weight=capitalized_graph_weight)
+
+    graph |= capitalized_graph
+    return graph
+
+
+def generator_main(file_name: str, graphs: Dict[str, 'pynini.FstLike']):
+    """
+    Exports graph as OpenFst finite state archive (FAR) file with given file name and rule name.
+
+    Args:
+        file_name: exported file name
+        graphs: Mapping of a rule name and Pynini WFST graph to be exported
+    """
+    exporter = export.Exporter(file_name)
+    for rule, graph in graphs.items():
+        exporter[rule] = graph.optimize()
+    exporter.close()
+    logging.info(f'Created {file_name}')
+
+
+def get_plurals(fst):
+    """
+    Given singular returns plurals
+
+    Args:
+        fst: Fst
+
+    Returns plurals to given singular forms
+    """
+    return SINGULAR_TO_PLURAL @ fst
+
+
+def get_singulars(fst):
+    """
+    Given plural returns singulars
+
+    Args:
+        fst: Fst
+
+    Returns singulars to given plural forms
+    """
+    return PLURAL_TO_SINGULAR @ fst
+
+
+def convert_space(fst) -> 'pynini.FstLike':
+    """
+    Converts space to nonbreaking space.
+    Used only in tagger grammars for transducing token values within quotes, e.g. name: "hello kitty"
+    This is making transducer significantly slower, so only use when there could be potential spaces within quotes, otherwise leave it.
+
+    Args:
+        fst: input fst
+
+    Returns output fst where breaking spaces are converted to non breaking spaces
+    """
+    return fst @ pynini.cdrewrite(pynini.cross(NEMO_SPACE, NEMO_NON_BREAKING_SPACE), "", "", NEMO_SIGMA)
+
+
+def string_map_cased(input_file: str, input_case: str = INPUT_LOWER_CASED):
+    labels = load_labels(input_file)
+
+    if input_case == INPUT_CASED:
+        additional_labels = []
+        for written, spoken, *weight in labels:
+            written_capitalized = written[0].upper() + written[1:]
+            additional_labels.extend(
+                [
+                    [written_capitalized, spoken.capitalize()],  # first letter capitalized
+                    [
+                        written_capitalized,
+                        spoken.upper().replace(" AND ", " and "),
+                    ],  # # add pairs with the all letters capitalized
+                ]
+            )
+
+            spoken_no_space = spoken.replace(" ", "")
+            # add abbreviations without spaces (both lower and upper case), i.e. "BMW" not "B M W"
+            if len(spoken) == (2 * len(spoken_no_space) - 1):
+                logging.debug(f"This is weight {weight}")
+                if len(weight) == 0:
+                    additional_labels.extend(
+                        [[written, spoken_no_space], [written_capitalized, spoken_no_space.upper()]]
+                    )
+                else:
+                    additional_labels.extend(
+                        [
+                            [written, spoken_no_space, weight[0]],
+                            [written_capitalized, spoken_no_space.upper(), weight[0]],
+                        ]
+                    )
+        labels += additional_labels
+
+    whitelist = pynini.string_map(labels).invert().optimize()
+    return whitelist
+
+
+class GraphFst:
+    """
+    Base class for all grammar fsts.
+
+    Args:
+        name: name of grammar class
+        kind: either 'classify' or 'verbalize'
+        deterministic: if True will provide a single transduction option,
+            for False multiple transduction are generated (used for audio-based normalization)
+    """
+
+    def __init__(self, name: str, kind: str, deterministic: bool = True):
+        self.name = name
+        self.kind = kind
+        self._fst = None
+        self.deterministic = deterministic
+
+        self.far_path = Path(os.path.dirname(__file__) + '/grammars/' + kind + '/' + name + '.far')
+        if self.far_exist():
+            self._fst = Far(self.far_path, mode="r", arc_type="standard", far_type="default").get_fst()
+
+    def far_exist(self) -> bool:
+        """
+        Returns true if FAR can be loaded
+        """
+        return self.far_path.exists()
+
+    @property
+    def fst(self) -> 'pynini.FstLike':
+        return self._fst
+
+    @fst.setter
+    def fst(self, fst):
+        self._fst = fst
+
+    def add_tokens(self, fst) -> 'pynini.FstLike':
+        """
+        Wraps class name around to given fst
+
+        Args:
+            fst: input fst
+
+        Returns:
+            Fst: fst
+        """
+        return pynutil.insert(f"{self.name} {{ ") + fst + pynutil.insert(" }")
+
+    def delete_tokens(self, fst) -> 'pynini.FstLike':
+        """
+        Deletes class name wrap around output of given fst
+
+        Args:
+            fst: input fst
+
+        Returns:
+            Fst: fst
+        """
+        res = (
+            pynutil.delete(f"{self.name}")
+            + delete_space
+            + pynutil.delete("{")
+            + delete_space
+            + fst
+            + delete_space
+            + pynutil.delete("}")
+        )
+        return res @ pynini.cdrewrite(pynini.cross(u"\u00a0", " "), "", "", NEMO_SIGMA)

nemo_text_processing/inverse_text_normalization/ko/taggers/__init__.py

@@ -0,0 +1,13 @@
+# Copyright (c) 2025, NVIDIA CORPORATION.  All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.