import os from torchaudio.datasets import speechcommands from ..common_utils import ( TempDirMixin, TorchaudioTestCase, get_whitenoise, normalize_wav, save_wav, ) LABELS = [ "bed", "bird", "cat", "dog", "down", "eight", "five", "follow", "forward", "four", "go", "happy", "house", "learn", "left", "marvin", "nine", "no", "off", "on", "one", "right", "seven", "sheila", "six", "stop", "three", "tree", "two", "up", "visual", "wow", "yes", "zero", ] class TestSpeechCommands(TempDirMixin, TorchaudioTestCase): backend = "default" root_dir = None samples = [] @classmethod def setUp(cls): cls.root_dir = cls.get_base_temp_dir() dataset_dir = os.path.join( cls.root_dir, speechcommands.FOLDER_IN_ARCHIVE, speechcommands.URL ) os.makedirs(dataset_dir, exist_ok=True) sample_rate = 16000 # 16kHz sample rate seed = 0 for label in LABELS: path = os.path.join(dataset_dir, label) os.makedirs(path, exist_ok=True) for j in range(2): # generate hash ID for speaker speaker = "{:08x}".format(j) for utterance in range(3): filename = f"{speaker}{speechcommands.HASH_DIVIDER}{utterance}.wav" file_path = os.path.join(path, filename) seed += 1 data = get_whitenoise( sample_rate=sample_rate, duration=0.01, n_channels=1, dtype="int16", seed=seed, ) save_wav(file_path, data, sample_rate) sample = ( normalize_wav(data), sample_rate, label, speaker, utterance, ) cls.samples.append(sample) def testSpeechCommands(self): dataset = speechcommands.SPEECHCOMMANDS(self.root_dir) print(dataset._path) num_samples = 0 for i, (data, sample_rate, label, speaker_id, utterance_number) in enumerate( dataset ): self.assertEqual(data, self.samples[i][0], atol=5e-5, rtol=1e-8) assert sample_rate == self.samples[i][1] assert label == self.samples[i][2] assert speaker_id == self.samples[i][3] assert utterance_number == self.samples[i][4] num_samples += 1 assert num_samples == len(self.samples)