Added test for CMUArctic Dataset (#829)

test/assets/ARCTIC/cmu_us_aew_arctic/etc/txt.done.data

-( arctic_a0024 "This is the test text." )

test/datasets/cmuarctic_test.py

+import os
+
+from torchaudio.datasets import cmuarctic
+
+from ..common_utils import (
+    TempDirMixin,
+    TorchaudioTestCase,
+    get_whitenoise,
+    save_wav,
+    normalize_wav,
+)
+
+
+class TestCMUARCTIC(TempDirMixin, TorchaudioTestCase):
+    backend = "default"
+
+    root_dir = None
+    samples = []
+
+    @classmethod
+    def setUpClass(cls):
+        cls.root_dir = cls.get_base_temp_dir()
+        sample_rate = 16000
+        utterance = "This is a test utterance."
+
+        base_dir = os.path.join(cls.root_dir, "ARCTIC", "cmu_us_aew_arctic")
+        txt_dir = os.path.join(base_dir, "etc")
+        os.makedirs(txt_dir, exist_ok=True)
+        txt_file = os.path.join(txt_dir, "txt.done.data")
+        audio_dir = os.path.join(base_dir, "wav")
+        os.makedirs(audio_dir, exist_ok=True)
+
+        seed = 42
+        with open(txt_file, "w") as txt:
+            for c in ["a", "b"]:
+                for i in range(5):
+                    utterance_id = f"arctic_{c}{i:04d}"
+                    path = os.path.join(audio_dir, f"{utterance_id}.wav")
+                    data = get_whitenoise(
+                        sample_rate=sample_rate,
+                        duration=3,
+                        n_channels=1,
+                        dtype="int16",
+                        seed=seed,
+                    )
+                    save_wav(path, data, sample_rate)
+                    sample = (
+                        normalize_wav(data),
+                        sample_rate,
+                        utterance,
+                        utterance_id.split("_")[1],
+                    )
+                    cls.samples.append(sample)
+                    txt.write(f'( {utterance_id} "{utterance}" )\n')
+                    seed += 1
+
+    def test_cmuarctic(self):
+        dataset = cmuarctic.CMUARCTIC(self.root_dir)
+        n_ite = 0
+        for i, (waveform, sample_rate, utterance, utterance_id) in enumerate(dataset):
+            expected_sample = self.samples[i]
+            assert sample_rate == expected_sample[1]
+            assert utterance == expected_sample[2]
+            assert utterance_id == expected_sample[3]
+            self.assertEqual(expected_sample[0], waveform, atol=5e-5, rtol=1e-8)
+            n_ite += 1
+        assert n_ite == len(self.samples)

test/datasets/datasets_test.py

 from torchaudio.datasets.librispeech import LIBRISPEECH
 from torchaudio.datasets.speechcommands import SPEECHCOMMANDS
 from torchaudio.datasets.vctk import VCTK
-from torchaudio.datasets.cmuarctic import CMUARCTIC
 
 from ..common_utils import (
     TorchaudioTestCase,
@@ -16,7 +15,3 @@ class TestDatasets(TorchaudioTestCase):
     def test_vctk(self):
         data = VCTK(self.path)
         data[0]
-
-    def test_cmuarctic(self):
-        data = CMUARCTIC(self.path)
-        data[0]