add unittest for vocabulary parameters

This commit is contained in:
Edresson Casanova 2020-03-05 17:44:47 -03:00
parent 36235c5e3f
commit 7ffc102542
3 changed files with 43 additions and 13 deletions

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@ -19,6 +19,16 @@
"mel_fmax": 7600, // maximum freq level for mel-spec. Tune for dataset!!
"do_trim_silence": false
},
"characters":{
"pad": "_",
"eos": "~",
"bos": "^",
"characters": "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!'(),-.:;? ",
"punctuations":"!'(),-.:;? ",
"phonemes":"iyɨʉɯuɪʏʊeøɘəɵɤoɛœɜɞʌɔæɐaɶɑɒᵻʘɓǀɗǃʄǂɠǁʛpbtdʈɖcɟkɡʔɴŋɲɳnɱmʙrʀⱱɾɽɸβfvθðszʃʒʂʐçʝxɣχʁħʕhɦɬɮʋɹɻjɰlɭʎʟˈˌːˑʍwɥʜʢʡɕʑɺɧɚ˞ɫ"
},
"hidden_size": 128,
"embedding_size": 256,
"text_cleaner": "english_cleaners",

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@ -1,7 +1,14 @@
import os
# pylint: disable=unused-wildcard-import
# pylint: disable=wildcard-import
# pylint: disable=unused-import
import unittest
import torch as T
from TTS.utils.text import *
from TTS.tests import get_tests_path
from TTS.utils.generic_utils import load_config
TESTS_PATH = get_tests_path()
conf = load_config(os.path.join(TESTS_PATH, 'test_config.json'))
def test_phoneme_to_sequence():
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!"
@ -9,67 +16,80 @@ def test_phoneme_to_sequence():
lang = "en-us"
sequence = phoneme_to_sequence(text, text_cleaner, lang)
text_hat = sequence_to_phoneme(sequence)
sequence_with_params = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
gt = "ɹiːsənt ɹɪːtʃ æt hɑːɹvɚd hɐz ʃoʊn mɛdᵻteɪɾɪŋ fɔːɹ æz lɪɾəl æz eɪt wiːks kæn æktʃuːəli ɪnkɹiːs, ðə ɡɹeɪ mæɾɚɹ ɪnðə pɑːɹts ʌvðə bɹeɪn ɹɪspɑːnsəbəl fɔːɹ ɪmoʊʃənəl ɹɛɡjuːleɪʃən ænd lɜːnɪŋ!"
assert text_hat == gt
assert text_hat == text_hat_with_params == gt
# multiple punctuations
text = "Be a voice, not an! echo?"
sequence = phoneme_to_sequence(text, text_cleaner, lang)
text_hat = sequence_to_phoneme(sequence)
sequence_with_params = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ?"
print(text_hat)
print(len(sequence))
assert text_hat == gt
assert text_hat == text_hat_with_params == gt
# not ending with punctuation
text = "Be a voice, not an! echo"
sequence = phoneme_to_sequence(text, text_cleaner, lang)
text_hat = sequence_to_phoneme(sequence)
sequence_with_params = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ"
print(text_hat)
print(len(sequence))
assert text_hat == gt
assert text_hat == text_hat_with_params == gt
# original
text = "Be a voice, not an echo!"
sequence = phoneme_to_sequence(text, text_cleaner, lang)
text_hat = sequence_to_phoneme(sequence)
sequence_with_params = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
gt = "biː ɐ vɔɪs, nɑːt ɐn ɛkoʊ!"
print(text_hat)
print(len(sequence))
assert text_hat == gt
assert text_hat == text_hat_with_params == gt
# extra space after the sentence
text = "Be a voice, not an! echo. "
sequence = phoneme_to_sequence(text, text_cleaner, lang)
text_hat = sequence_to_phoneme(sequence)
sequence_with_params = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ."
print(text_hat)
print(len(sequence))
assert text_hat == gt
assert text_hat == text_hat_with_params == gt
# extra space after the sentence
text = "Be a voice, not an! echo. "
sequence = phoneme_to_sequence(text, text_cleaner, lang, True)
text_hat = sequence_to_phoneme(sequence)
sequence_with_params = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
gt = "^biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ.~"
print(text_hat)
print(len(sequence))
assert text_hat == gt
assert text_hat == text_hat_with_params == gt
# padding char
text = "_Be a _voice, not an! echo_"
sequence = phoneme_to_sequence(text, text_cleaner, lang)
text_hat = sequence_to_phoneme(sequence)
sequence_with_params = phoneme_to_sequence(text, text_cleaner, lang, tp=conf.characters)
text_hat_with_params = sequence_to_phoneme(sequence, tp=conf.characters)
gt = "biː ɐ vɔɪs, nɑːt ɐn! ɛkoʊ"
print(text_hat)
print(len(sequence))
assert text_hat == gt
assert text_hat == text_hat_with_params == gt
def test_text2phone():
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!"
gt = "ɹ|iː|s|ə|n|t| |ɹ|ɪ|s|ɜː|tʃ| |æ|t| |h|ɑːɹ|v|ɚ|d| |h|ɐ|z| |ʃ|oʊ|n| |m|ɛ|d|ᵻ|t|eɪ|ɾ|ɪ|ŋ| |f|ɔː|ɹ| |æ|z| |l|ɪ|ɾ|əl| |æ|z| |eɪ|t| |w|iː|k|s| |k|æ|n| |æ|k|tʃ|uː|əl|i| |ɪ|n|k|ɹ|iː|s|,| |ð|ə| |ɡ|ɹ|eɪ| |m|æ|ɾ|ɚ|ɹ| |ɪ|n|ð|ə| |p|ɑːɹ|t|s| |ʌ|v|ð|ə| |b|ɹ|eɪ|n| |ɹ|ɪ|s|p|ɑː|n|s|ə|b|əl| |f|ɔː|ɹ| |ɪ|m|oʊ|ʃ|ə|n|əl| |ɹ|ɛ|ɡ|j|uː|l|eɪ|ʃ|ə|n| |æ|n|d| |l|ɜː|n|ɪ|ŋ|!"
lang = "en-us"
ph = text2phone(text, lang)
assert gt == ph, f"\n{phonemes} \n vs \n{gt}"
assert gt == ph, f"\n{phonemes} \n vs \n{gt}"

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@ -5,9 +5,9 @@ Defines the set of symbols used in text input to the model.
The default is a set of ASCII characters that works well for English or text that has been run
through Unidecode. For other data, you can modify _characters. See TRAINING_DATA.md for details.
'''
def make_symbols(characters, phnms, punctuations='!\'(),-.:;? ', pad='_', eos='~', bos='^'):
def make_symbols(characters, phonemes, punctuations='!\'(),-.:;? ', pad='_', eos='~', bos='^'):# pylint: disable=redefined-outer-name
''' Function to create symbols and phonemes '''
_phonemes_sorted = sorted(list(phnms))
_phonemes_sorted = sorted(list(phonemes))
# Prepend "@" to ARPAbet symbols to ensure uniqueness (some are the same as uppercase letters):
_arpabet = ['@' + s for s in _phonemes_sorted]