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

59 lines
1.8 KiB
Python

# Copyright (c) 2022, 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.collections.common.tokenizers import TokenizerSpec
from nemo.collections.common.tokenizers.text_to_speech.tts_tokenizers import EnglishPhonemesTokenizer
from nemo.collections.tts.g2p.models.en_us_arpabet import EnglishG2p
__all__ = ['TextToSpeechTokenizer']
class TextToSpeechTokenizer(TokenizerSpec):
def __init__(self, phoneme_dict, heteronyms):
self.g2p = EnglishG2p(phoneme_dict=phoneme_dict, heteronyms=heteronyms)
self.tokenizer = EnglishPhonemesTokenizer(
self.g2p, stresses=True, chars=True, pad_with_space=True, add_blank_at=True
)
self.vocab_size = len(self.tokenizer.tokens)
def text_to_ids(self, text):
return self.tokenizer.encode(text)
def text_to_tokens(self, text):
return self.g2p(text)
def tokens_to_text(self, tokens):
pass
def tokens_to_ids(self, tokens):
pass
def ids_to_tokens(self, ids):
pass
def ids_to_text(self, ids):
pass
@property
def pad_id(self):
return self.tokenizer.pad
@property
def bos_id(self):
return self.tokenizer.pad
@property
def eos_id(self):
return self.tokenizer.pad