mirror of https://github.com/coqui-ai/TTS.git
phonem extraction for training
Eren Golge
parent
5e6e3d166a
commit
8e22147a19
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@ -6,7 +6,7 @@ import torch
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import random
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from torch.utils.data import Dataset
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from utils.text import text_to_sequence
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from utils.text import text_to_sequence, phoneme_to_sequence
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from utils.data import (prepare_data, pad_per_step, prepare_tensor,
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prepare_stop_target)
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@ -2,16 +2,26 @@
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import re
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from utils.text import cleaners
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from utils.text.symbols import symbols
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from utils.text.symbols import symbols, phonemes
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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)}
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_phonemes_to_id = {s: i for i, s in enumerate(phonemes)}
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_id_to_phonemes = {i: s for i, s in enumerate(phonemes)}
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# Regular expression matching text enclosed in curly braces:
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_curly_re = re.compile(r'(.*?)\{(.+?)\}(.*)')
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def phoneme_to_sequence(text, cleaner_names):
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sequence = []
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sequence += _phonem_to_sequence(_clean_text(text, cleaner_names))
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sequence.append(_phonemes_to_id['~'])
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return sequence
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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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@ -69,9 +79,17 @@ def _symbols_to_sequence(symbols):
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return [_symbol_to_id[s] for s in symbols if _should_keep_symbol(s)]
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def _phonem_to_sequence(phonemes):
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return [_phonemes_to_id[s] for s in phonemes if _should_keep_phonem(s)]
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def _arpabet_to_sequence(text):
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return _symbols_to_sequence(['@' + s for s in text.split()])
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def _should_keep_symbol(s):
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return s in _symbol_to_id and s is not '_' and s is not '~'
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def _should_keep_phonem(p):
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return p in _phonemes_to_id and p is not '_' and p is not '~'
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@ -12,7 +12,7 @@ hyperparameter. Some cleaners are English-specific. You'll typically want to use
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import re
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from unidecode import unidecode
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from .numbers import normalize_numbers
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from .number_norm import normalize_numbers
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# Regular expression matching whitespace:
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_whitespace_re = re.compile(r'\s+')
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@ -1,19 +1,75 @@
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# -*- coding: utf-8 -*-
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import re
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import phonemizer
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valid_symbols = [
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'AA', 'AA0', 'AA1', 'AA2', 'AE', 'AE0', 'AE1', 'AE2', 'AH', 'AH0', 'AH1',
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'AH2', 'AO', 'AO0', 'AO1', 'AO2', 'AW', 'AW0', 'AW1', 'AW2', 'AY', 'AY0',
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'AY1', 'AY2', 'B', 'CH', 'D', 'DH', 'EH', 'EH0', 'EH1', 'EH2', 'ER', 'ER0',
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'ER1', 'ER2', 'EY', 'EY0', 'EY1', 'EY2', 'F', 'G', 'HH', 'IH', 'IH0',
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'IH1', 'IH2', 'IY', 'IY0', 'IY1', 'IY2', 'JH', 'K', 'L', 'M', 'N', 'NG',
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'OW', 'OW0', 'OW1', 'OW2', 'OY', 'OY0', 'OY1', 'OY2', 'P', 'R', 'S', 'SH',
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'T', 'TH', 'UH', 'UH0', 'UH1', 'UH2', 'UW', 'UW0', 'UW1', 'UW2', 'V', 'W',
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'Y', 'Z', 'ZH'
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]
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# valid_symbols = [
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# 'AA', 'AA0', 'AA1', 'AA2', 'AE', 'AE0', 'AE1', 'AE2', 'AH', 'AH0', 'AH1',
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# 'AH2', 'AO', 'AO0', 'AO1', 'AO2', 'AW', 'AW0', 'AW1', 'AW2', 'AY', 'AY0',
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# 'AY1', 'AY2', 'B', 'CH', 'D', 'DH', 'EH', 'EH0', 'EH1', 'EH2', 'ER', 'ER0',
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# 'ER1', 'ER2', 'EY', 'EY0', 'EY1', 'EY2', 'F', 'G', 'HH', 'IH', 'IH0',
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# 'IH1', 'IH2', 'IY', 'IY0', 'IY1', 'IY2', 'JH', 'K', 'L', 'M', 'N', 'NG',
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# 'OW', 'OW0', 'OW1', 'OW2', 'OY', 'OY0', 'OY1', 'OY2', 'P', 'R', 'S', 'SH',
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# 'T', 'TH', 'UH', 'UH0', 'UH1', 'UH2', 'UW', 'UW0', 'UW1', 'UW2', 'V', 'W',
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# 'Y', 'Z', 'ZH'
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# ]
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_valid_symbol_set = set(valid_symbols)
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_phonemes = {
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'aa',
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'ae',
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'ah',
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'ao',
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'aw',
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'ax',
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'ay',
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'b',
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'ch',
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'd',
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'dh',
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'eh',
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'ey',
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'f',
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'g',
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'hh',
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'i',
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'ih',
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'iy',
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'jh',
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'k',
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'l',
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'm',
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'n',
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'ng',
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'ow',
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'oy',
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'p',
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'pau',
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'r',
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's',
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'sh',
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'ssil',
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't',
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'th',
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'uh',
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'uw',
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'v',
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'w',
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'y',
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'z'
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}
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_phonemes = set(_phonemes)
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def text2phone(text):
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seperator = phonemizer.separator.Separator('', '', ' ')
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ph = phonemizer.phonemize(text, separator=seperator)
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ph = ph.split(' ')
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ph.remove('')
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result = [char2code[p] for p in ph]
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return result
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class CMUDict:
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@ -1,129 +0,0 @@
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import re
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_comma_number_re = re.compile(r'([0-9][0-9\,]+[0-9])')
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_decimal_number_re = re.compile(r'([0-9]+\.[0-9]+)')
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_pounds_re = re.compile(r'£([0-9\,]*[0-9]+)')
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_dollars_re = re.compile(r'\$([0-9\.\,]*[0-9]+)')
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_ordinal_re = re.compile(r'([0-9]+)(st|nd|rd|th)')
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_number_re = re.compile(r'[0-9]+')
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_units = [
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'', 'one', 'two', 'three', 'four', 'five', 'six', 'seven', 'eight', 'nine',
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'ten', 'eleven', 'twelve', 'thirteen', 'fourteen', 'fifteen', 'sixteen',
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'seventeen', 'eighteen', 'nineteen'
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]
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_tens = [
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'',
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'ten',
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'twenty',
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'thirty',
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'forty',
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'fifty',
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'sixty',
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'seventy',
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'eighty',
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'ninety',
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]
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_digit_groups = [
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'',
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'thousand',
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'million',
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'billion',
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'trillion',
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'quadrillion',
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]
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_ordinal_suffixes = [
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('one', 'first'),
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('two', 'second'),
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('three', 'third'),
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('five', 'fifth'),
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('eight', 'eighth'),
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('nine', 'ninth'),
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('twelve', 'twelfth'),
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('ty', 'tieth'),
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]
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def _remove_commas(m):
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return m.group(1).replace(',', '')
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def _expand_decimal_point(m):
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return m.group(1).replace('.', ' point ')
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def _expand_dollars(m):
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match = m.group(1)
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parts = match.split('.')
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if len(parts) > 2:
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return match + ' dollars' # Unexpected format
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dollars = int(parts[0]) if parts[0] else 0
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cents = int(parts[1]) if len(parts) > 1 and parts[1] else 0
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if dollars and cents:
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dollar_unit = 'dollar' if dollars == 1 else 'dollars'
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cent_unit = 'cent' if cents == 1 else 'cents'
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return '%s %s, %s %s' % (dollars, dollar_unit, cents, cent_unit)
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elif dollars:
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dollar_unit = 'dollar' if dollars == 1 else 'dollars'
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return '%s %s' % (dollars, dollar_unit)
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elif cents:
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cent_unit = 'cent' if cents == 1 else 'cents'
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return '%s %s' % (cents, cent_unit)
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else:
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return 'zero dollars'
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def _standard_number_to_words(n, digit_group):
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parts = []
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if n >= 1000:
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# Format next higher digit group.
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parts.append(_standard_number_to_words(n // 1000, digit_group + 1))
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n = n % 1000
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if n >= 100:
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parts.append('%s hundred' % _units[n // 100])
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if n % 100 >= len(_units):
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parts.append(_tens[(n % 100) // 10])
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parts.append(_units[(n % 100) % 10])
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else:
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parts.append(_units[n % 100])
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if n > 0:
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parts.append(_digit_groups[digit_group])
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return ' '.join([x for x in parts if x])
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def _number_to_words(n):
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# Handle special cases first, then go to the standard case:
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if n >= 1000000000000000000:
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return str(n) # Too large, just return the digits
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elif n == 0:
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return 'zero'
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elif n % 100 == 0 and n % 1000 != 0 and n < 3000:
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return _standard_number_to_words(n // 100, 0) + ' hundred'
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else:
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return _standard_number_to_words(n, 0)
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def _expand_number(m):
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return _number_to_words(int(m.group(0)))
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def _expand_ordinal(m):
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num = _number_to_words(int(m.group(1)))
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for suffix, replacement in _ordinal_suffixes:
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if num.endswith(suffix):
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return num[:-len(suffix)] + replacement
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return num + 'th'
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def normalize_numbers(text):
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text = re.sub(_comma_number_re, _remove_commas, text)
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text = re.sub(_pounds_re, r'\1 pounds', text)
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text = re.sub(_dollars_re, _expand_dollars, text)
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text = re.sub(_decimal_number_re, _expand_decimal_point, text)
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text = re.sub(_ordinal_re, _expand_ordinal, text)
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text = re.sub(_number_re, _expand_number, text)
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return text
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@ -12,10 +12,11 @@ _eos = '~'
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_characters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!\'(),-.:;? '
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# Prepend "@" to ARPAbet symbols to ensure uniqueness (some are the same as uppercase letters):
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_arpabet = ['@' + s for s in cmudict.valid_symbols]
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_arpabet = ['@' + s for s in cmudict._phonemes]
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# Export all symbols:
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symbols = [_pad, _eos] + list(_characters) + _arpabet
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phonemes = [_pad, _eos] + cmudict._phonemes + list('!\'(),-.:;?')
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if __name__ == '__main__':
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print(symbols)
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