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chore: import upstream snapshot with attribution
2026-07-13 13:28:58 +08:00

42 行
1.6 KiB
Python

# Copyright (c) 2023, NVIDIA CORPORATION & AFFILIATES. 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 abc import ABC, abstractmethod
from typing import Optional
class BaseG2p(ABC):
def __init__(
self,
phoneme_dict=None,
word_tokenize_func=lambda x: x,
apply_to_oov_word=None,
mapping_file: Optional[str] = None,
):
"""Abstract class for creating an arbitrary module to convert grapheme words
to phoneme sequences, leave unchanged, or use apply_to_oov_word.
Args:
phoneme_dict: Arbitrary representation of dictionary (phoneme -> grapheme) for known words.
word_tokenize_func: Function for tokenizing text to words.
apply_to_oov_word: Function that will be applied to out of phoneme_dict word.
"""
self.phoneme_dict = phoneme_dict
self.word_tokenize_func = word_tokenize_func
self.apply_to_oov_word = apply_to_oov_word
self.mapping_file = mapping_file
@abstractmethod
def __call__(self, text: str) -> str:
pass