54 lines
1.7 KiB
Python
54 lines
1.7 KiB
Python
""" from https://github.com/keithito/tacotron """
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from matcha.text import cleaners
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from matcha.text.symbols import symbols
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# Mappings from symbol to numeric ID and vice versa:
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_symbol_to_id = {s: i for i, s in enumerate(symbols)}
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_id_to_symbol = {i: s for i, s in enumerate(symbols)} # pylint: disable=unnecessary-comprehension
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def text_to_sequence(text, cleaner_names):
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"""Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
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Args:
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text: string to convert to a sequence
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cleaner_names: names of the cleaner functions to run the text through
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Returns:
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List of integers corresponding to the symbols in the text
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"""
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sequence = []
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clean_text = _clean_text(text, cleaner_names)
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for symbol in clean_text:
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symbol_id = _symbol_to_id[symbol]
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sequence += [symbol_id]
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return sequence, clean_text
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def cleaned_text_to_sequence(cleaned_text):
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"""Converts a string of text to a sequence of IDs corresponding to the symbols in the text.
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Args:
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text: string to convert to a sequence
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Returns:
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List of integers corresponding to the symbols in the text
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"""
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sequence = [_symbol_to_id[symbol] for symbol in cleaned_text]
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return sequence
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def sequence_to_text(sequence):
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"""Converts a sequence of IDs back to a string"""
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result = ""
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for symbol_id in sequence:
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s = _id_to_symbol[symbol_id]
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result += s
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return result
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def _clean_text(text, cleaner_names):
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for name in cleaner_names:
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cleaner = getattr(cleaners, name)
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if not cleaner:
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raise Exception("Unknown cleaner: %s" % name)
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text = cleaner(text)
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return text
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