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import csv
import os
from pathlib import Path
from typing import Dict, Tuple
from torch import Tensor
from torchaudio.datasets import COMMONVOICE
from torchaudio_unittest.common_utils import get_whitenoise, normalize_wav, save_wav, TempDirMixin, TorchaudioTestCase
_ORIGINAL_EXT_AUDIO = COMMONVOICE._ext_audio
_SAMPLE_RATE = 48000
_HEADERS = ["client_ids", "path", "sentence", "up_votes", "down_votes", "age", "gender", "accent"]
_EN_TRAIN_CSV_CONTENTS = [
[
"9d16c5d980247861130e0480e2719f448be73d86a496c36d01a477cbdecd8cfd1399403d7a77bf458d211a70711b2da0845c",
"common_voice_en_18885784.wav",
"He was accorded a State funeral, and was buried in Drayton and Toowoomba Cemetery.",
"2",
"0",
"",
"",
"",
],
[
"c82eb9291328620f06025a1f8112b909099e447e485e99236cb87df008650250e79fea5ca772061fb6a370830847b9c44d20",
"common_voice_en_556542.wav",
"Once more into the breach",
"2",
"0",
"thirties",
"male",
"us",
],
[
"f74d880c5ad4c5917f314a604d3fc4805159d255796fb9f8defca35333ecc002bdf53dc463503c12674ea840b21b4a507b7c",
"common_voice_en_18607573.wav",
"Caddy, show Miss Clare and Miss Summerson their rooms.",
"2",
"0",
"twenties",
"male",
"canada",
],
]
_FR_TRAIN_CSV_CONTENTS = [
[
"a2e8e1e1cc74d08c92a53d7b9ff84e077eb90410edd85b8882f16fd037cecfcb6a19413c6c63ce6458cfea9579878fa91cef"
"18343441c601cae0597a4b0d3144",
"89e67e7682b36786a0b4b4022c4d42090c86edd96c78c12d30088e62522b8fe466ea4912e6a1055dfb91b296a0743e0a2bbe"
"16cebac98ee5349e3e8262cb9329",
"Or sur ce point nous n’avons aucune réponse de votre part.",
"2",
"0",
"twenties",
"male",
"france",
],
[
"a2e8e1e1cc74d08c92a53d7b9ff84e077eb90410edd85b8882f16fd037cecfcb6a19413c6c63ce6458cfea9579878fa91cef18"
"343441c601cae0597a4b0d3144",
"87d71819a26179e93acfee149d0b21b7bf5e926e367d80b2b3792d45f46e04853a514945783ff764c1fc237b4eb0ee2b0a7a7"
"cbd395acbdfcfa9d76a6e199bbd",
"Monsieur de La Verpillière, laissez parler le ministre",
"2",
"0",
"twenties",
"male",
"france",
],
]
def get_mock_dataset(root_dir, train_csv_contents, ext_audio) -> Tuple[Tensor, int, Dict[str, str]]:
"""
prepares mocked dataset
"""
mocked_data = []
# Note: extension is changed to wav for the sake of test
# Note: the first content is missing values for `age`, `gender` and `accent` as in the original data.
# Tsv file name difference does not mean different subset, testing as a whole dataset here
tsv_filename = os.path.join(root_dir, "train.tsv")
audio_base_path = os.path.join(root_dir, "clips")
os.makedirs(audio_base_path, exist_ok=True)
with open(tsv_filename, "w", newline="") as tsv:
writer = csv.writer(tsv, delimiter="\t")
writer.writerow(_HEADERS)
for i, content in enumerate(train_csv_contents):
content[2] = str(content[2].encode("utf-8"))
writer.writerow(content)
if not content[1].endswith(ext_audio):
audio_path = os.path.join(audio_base_path, content[1] + ext_audio)
else:
audio_path = os.path.join(audio_base_path, content[1])
data = get_whitenoise(sample_rate=_SAMPLE_RATE, duration=1, n_channels=1, seed=i, dtype="float32")
save_wav(audio_path, data, _SAMPLE_RATE)
# Append data entry
mocked_data.append((normalize_wav(data), _SAMPLE_RATE, dict(zip(_HEADERS, content))))
return mocked_data
def get_mock_dataset_en(root_dir, ext_audio) -> Tuple[Tensor, int, Dict[str, str]]:
"""
prepares english mocked dataset
"""
return get_mock_dataset(root_dir, _EN_TRAIN_CSV_CONTENTS, ext_audio)
def get_mock_dataset_fr(root_dir, ext_audio) -> Tuple[Tensor, int, Dict[str, str]]:
"""
prepares french mocked dataset
"""
return get_mock_dataset(root_dir, _FR_TRAIN_CSV_CONTENTS, ext_audio)
class BaseTestCommonVoice(TempDirMixin):
root_dir = None
data = None
@classmethod
def setUpClass(cls):
super().setUpClass()
cls.root_dir = cls.get_base_temp_dir()
COMMONVOICE._ext_audio = ".wav"
@classmethod
def tearDownClass(cls):
super().tearDownClass()
COMMONVOICE._ext_audio = _ORIGINAL_EXT_AUDIO
def _test_commonvoice(self, dataset):
n_ite = 0
for i, (waveform, sample_rate, dictionary) in enumerate(dataset):
expected_dictionary = self.data[i][2]
expected_data = self.data[i][0]
self.assertEqual(expected_data, waveform, atol=5e-5, rtol=1e-8)
assert sample_rate == _SAMPLE_RATE
assert dictionary == expected_dictionary
n_ite += 1
assert n_ite == len(self.data)
class TestCommonVoiceEN(BaseTestCommonVoice, TorchaudioTestCase):
root_dir = None
@classmethod
def setUpClass(cls):
super().setUpClass()
cls.data = get_mock_dataset_en(cls.root_dir, COMMONVOICE._ext_audio)
def test_commonvoice_str(self):
dataset = COMMONVOICE(self.root_dir)
self._test_commonvoice(dataset)
def test_commonvoice_path(self):
dataset = COMMONVOICE(Path(self.root_dir))
self._test_commonvoice(dataset)
class TestCommonVoiceFR(BaseTestCommonVoice, TorchaudioTestCase):
root_dir = None
@classmethod
def setUpClass(cls):
super().setUpClass()
cls.data = get_mock_dataset_fr(cls.root_dir, COMMONVOICE._ext_audio)
def test_commonvoice_str(self):
dataset = COMMONVOICE(self.root_dir)
self._test_commonvoice(dataset)
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