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on
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Running
on
Zero
| # Copyright (c) 2024 Amphion. | |
| # | |
| # This source code is licensed under the MIT license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| import re | |
| """ | |
| Text clean time | |
| """ | |
| rep_map = { | |
| ":": ",", | |
| ";": ",", | |
| ",": ",", | |
| "。": ".", | |
| "!": "!", | |
| "?": "?", | |
| "\n": ".", | |
| "·": ",", | |
| "、": ",", | |
| "...": ".", | |
| "…": ".", | |
| "$": ".", | |
| "“": "", | |
| "”": "", | |
| "‘": "", | |
| "’": "", | |
| "(": "", | |
| ")": "", | |
| "(": "", | |
| ")": "", | |
| "《": "", | |
| "》": "", | |
| "【": "", | |
| "】": "", | |
| "[": "", | |
| "]": "", | |
| "—": "", | |
| "~": "-", | |
| "~": "-", | |
| "「": "", | |
| "」": "", | |
| "¿": "", | |
| "¡": "", | |
| } | |
| def collapse_whitespace(text): | |
| # Regular expression matching whitespace: | |
| _whitespace_re = re.compile(r"\s+") | |
| return re.sub(_whitespace_re, " ", text).strip() | |
| def remove_punctuation_at_begin(text): | |
| return re.sub(r"^[,.!?]+", "", text) | |
| def remove_aux_symbols(text): | |
| text = re.sub(r"[\<\>\(\)\[\]\"\«\»]+", "", text) | |
| return text | |
| def replace_symbols(text): | |
| text = text.replace(";", ",") | |
| text = text.replace("-", " ") | |
| text = text.replace(":", ",") | |
| return text | |
| def replace_punctuation(text): | |
| pattern = re.compile("|".join(re.escape(p) for p in rep_map.keys())) | |
| replaced_text = pattern.sub(lambda x: rep_map[x.group()], text) | |
| return replaced_text | |
| def text_normalize(text): | |
| text = replace_punctuation(text) | |
| text = replace_symbols(text) | |
| text = remove_aux_symbols(text) | |
| text = remove_punctuation_at_begin(text) | |
| text = collapse_whitespace(text) | |
| text = re.sub(r"([^\.,!\?\-…])$", r"\1", text) | |
| return text | |
| def german_to_ipa(text, text_tokenizer): | |
| if type(text) == str: | |
| text = text_normalize(text) | |
| phonemes = text_tokenizer(text) | |
| return phonemes | |
| else: | |
| for i, t in enumerate(text): | |
| text[i] = text_normalize(t) | |
| return text_tokenizer(text) | |