mirror of https://github.com/coqui-ai/TTS.git
Upgrade to gruut 2.0 (#882)
This commit is contained in:
Michael Hansen
GitHub
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commit
3bc043faeb
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@ -5,6 +5,7 @@ import re
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from typing import Dict, List
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import gruut
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from gruut_ipa import IPA
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from TTS.tts.utils.text import cleaners
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from TTS.tts.utils.text.chinese_mandarin.phonemizer import chinese_text_to_phonemes
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@ -32,7 +33,7 @@ PHONEME_PUNCTUATION_PATTERN = r"[" + _punctuations.replace(" ", "") + "]+"
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GRUUT_TRANS_TABLE = str.maketrans("g", "ɡ")
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def text2phone(text, language, use_espeak_phonemes=False):
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def text2phone(text, language, use_espeak_phonemes=False, keep_stress=False):
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"""Convert graphemes to phonemes.
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Parameters:
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text (str): text to phonemize
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@ -51,36 +52,44 @@ def text2phone(text, language, use_espeak_phonemes=False):
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ph = japanese_text_to_phonemes(text)
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return ph
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if gruut.is_language_supported(language):
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# Use gruut for phonemization
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phonemizer_args = {
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"remove_stress": True,
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"ipa_minor_breaks": False, # don't replace commas/semi-colons with IPA |
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"ipa_major_breaks": False, # don't replace periods with IPA ‖
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}
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if not gruut.is_language_supported(language):
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raise ValueError(f" [!] Language {language} is not supported for phonemization.")
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if use_espeak_phonemes:
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# Use a lexicon/g2p model train on eSpeak IPA instead of gruut IPA.
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# This is intended for backwards compatibility with TTS<=v0.0.13
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# pre-trained models.
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phonemizer_args["model_prefix"] = "espeak"
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# Use gruut for phonemization
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ph_list = []
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for sentence in gruut.sentences(text, lang=language, espeak=use_espeak_phonemes):
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for word in sentence:
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if word.is_break:
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# Use actual character for break phoneme (e.g., comma)
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if ph_list:
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# Join with previous word
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ph_list[-1].append(word.text)
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else:
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# First word is punctuation
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ph_list.append([word.text])
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elif word.phonemes:
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# Add phonemes for word
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word_phonemes = []
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ph_list = gruut.text_to_phonemes(
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text,
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lang=language,
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return_format="word_phonemes",
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phonemizer_args=phonemizer_args,
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)
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for word_phoneme in word.phonemes:
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if not keep_stress:
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# Remove primary/secondary stress
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word_phoneme = IPA.without_stress(word_phoneme)
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# Join and re-split to break apart dipthongs, suprasegmentals, etc.
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ph_words = ["|".join(word_phonemes) for word_phonemes in ph_list]
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ph = "| ".join(ph_words)
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word_phoneme = word_phoneme.translate(GRUUT_TRANS_TABLE)
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# Fix a few phonemes
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ph = ph.translate(GRUUT_TRANS_TABLE)
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return ph
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if word_phoneme:
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# Flatten phonemes
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word_phonemes.extend(word_phoneme)
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raise ValueError(f" [!] Language {language} is not supported for phonemization.")
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if word_phonemes:
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ph_list.append(word_phonemes)
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# Join and re-split to break apart dipthongs, suprasegmentals, etc.
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ph_words = ["|".join(word_phonemes) for word_phonemes in ph_list]
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ph = "| ".join(ph_words)
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return ph
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def intersperse(sequence, token):
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@ -23,6 +23,6 @@ coqpit
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mecab-python3==1.0.3
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unidic-lite==1.0.8
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# gruut+supported langs
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gruut[cs,de,es,fr,it,nl,pt,ru,sv]~=1.2.0
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gruut[cs,de,es,fr,it,nl,pt,ru,sv]~=2.0.0
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fsspec>=2021.04.0
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pyworld
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@ -9,12 +9,12 @@ LANG = "en-us"
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EXAMPLE_TEXT = "Recent research at Harvard has shown meditating for as little as 8 weeks can actually increase, the grey matter in the parts of the brain responsible for emotional regulation and learning!"
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EXPECTED_PHONEMES = "ɹ|iː|s|ə|n|t| ɹ|ᵻ|s|ɜː|tʃ| æ|t| h|ɑːɹ|v|ɚ|d| h|æ|z| ʃ|oʊ|n| m|ɛ|d|ᵻ|t|eɪ|ɾ|ɪ|ŋ| f|ɔːɹ| æ|z| l|ɪ|ɾ|əl| æ|z| eɪ|t| w|iː|k|s| k|æ|n| æ|k|tʃ|uː|əl|i| ɪ|ŋ|k|ɹ|iː|s| ,| ð|ə| ɡ|ɹ|eɪ| m|æ|ɾ|ɚ| ɪ|n| ð|ə| p|ɑːɹ|t|s| ʌ|v| ð|ə| b|ɹ|eɪ|n| ɹ|ᵻ|s|p|ɑː|n|s|ᵻ|b|əl| f|ɔːɹ| ɪ|m|oʊ|ʃ|ə|n|əl| ɹ|ɛ|ɡ|j|ʊ|l|eɪ|ʃ|ə|n| æ|n|d| l|ɜː|n|ɪ|ŋ| !"
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EXPECTED_PHONEMES = "ɹ|i|ː|s|ə|n|t| ɹ|ᵻ|s|ɜ|ː|t|ʃ| æ|ɾ| h|ɑ|ː|ɹ|v|ɚ|d| h|ɐ|z| ʃ|o|ʊ|n| m|ɛ|d|ᵻ|t|e|ɪ|ɾ|ɪ|ŋ| f|ɔ|ː|ɹ| æ|z| l|ɪ|ɾ|ə|l| æ|z| e|ɪ|t| w|i|ː|k|s| k|æ|ŋ| æ|k|t|ʃ|u|ː|ə|l|i| ɪ|ŋ|k|ɹ|i|ː|s|,| ð|ə| ɡ|ɹ|e|ɪ| m|æ|ɾ|ɚ| ɪ|n| ð|ə| p|ɑ|ː|ɹ|t|s| ʌ|v| ð|ə| b|ɹ|e|ɪ|n| ɹ|ᵻ|s|p|ɑ|ː|n|s|ᵻ|b|ə|l| f|ɔ|ː|ɹ| ɪ|m|o|ʊ|ʃ|ə|n|ə|l| ɹ|ɛ|ɡ|j|ʊ|l|e|ɪ|ʃ|ə|n| æ|n|d| l|ɜ|ː|n|ɪ|ŋ|!"
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# -----------------------------------------------------------------------------
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class TextProcessingTextCase(unittest.TestCase):
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class TextProcessingTestCase(unittest.TestCase):
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"""Tests for text to phoneme conversion"""
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def test_phoneme_to_sequence(self):
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@ -40,7 +40,7 @@ class TextProcessingTextCase(unittest.TestCase):
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sequence = phoneme_to_sequence(text, text_cleaner, LANG, add_blank=add_blank, use_espeak_phonemes=True)
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text_hat = sequence_to_phoneme(sequence)
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text_hat_with_params = sequence_to_phoneme(sequence)
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gt = "biː ɐ vɔɪs , nɑːt ɐn ! ɛkoʊ ?"
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gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ?"
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print(text_hat)
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print(len(sequence))
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self.assertEqual(text_hat, text_hat_with_params)
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@ -51,7 +51,7 @@ class TextProcessingTextCase(unittest.TestCase):
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sequence = phoneme_to_sequence(text, text_cleaner, LANG, add_blank=add_blank, use_espeak_phonemes=True)
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text_hat = sequence_to_phoneme(sequence)
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text_hat_with_params = sequence_to_phoneme(sequence)
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gt = "biː ɐ vɔɪs , nɑːt ɐn ! ɛkoʊ"
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gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ"
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print(text_hat)
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print(len(sequence))
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self.assertEqual(text_hat, text_hat_with_params)
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@ -62,7 +62,7 @@ class TextProcessingTextCase(unittest.TestCase):
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sequence = phoneme_to_sequence(text, text_cleaner, LANG, add_blank=add_blank, use_espeak_phonemes=True)
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text_hat = sequence_to_phoneme(sequence)
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text_hat_with_params = sequence_to_phoneme(sequence)
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gt = "biː ɐ vɔɪs , nɑːt ɐn ɛkoʊ !"
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gt = "biː ɐ vɔɪs, nɑːt ɐn ɛkoʊ!"
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print(text_hat)
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print(len(sequence))
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self.assertEqual(text_hat, text_hat_with_params)
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@ -73,7 +73,7 @@ class TextProcessingTextCase(unittest.TestCase):
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sequence = phoneme_to_sequence(text, text_cleaner, LANG, add_blank=add_blank, use_espeak_phonemes=True)
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text_hat = sequence_to_phoneme(sequence)
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text_hat_with_params = sequence_to_phoneme(sequence)
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gt = "biː ɐ vɔɪs , nɑːt ɐn ! ɛkoʊ ."
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gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ."
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print(text_hat)
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print(len(sequence))
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self.assertEqual(text_hat, text_hat_with_params)
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@ -86,7 +86,7 @@ class TextProcessingTextCase(unittest.TestCase):
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)
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text_hat = sequence_to_phoneme(sequence)
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text_hat_with_params = sequence_to_phoneme(sequence)
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gt = "^biː ɐ vɔɪs , nɑːt ɐn ! ɛkoʊ .~"
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gt = "^biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ.~"
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print(text_hat)
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print(len(sequence))
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self.assertEqual(text_hat, text_hat_with_params)
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