Add 3 augmentor classes and related unittests

deep_speech_2/tests/test_augmentor.py

@@ -11,49 +11,53 @@ import numpy as np
 
 random_seed=0
 #audio instance
-audio_data=[3.05175781e-05, -8.54492188e-04, -1.09863281e-03, -9.46044922e-04,\
-            -1.31225586e-03, -1.09863281e-03, -1.73950195e-03, -2.10571289e-03,\
-            -2.04467773e-03, -1.46484375e-03, -1.43432617e-03, -9.46044922e-04,\
-            -1.95312500e-03, -1.86157227e-03, -2.10571289e-03, -2.31933594e-03,\
-            -2.01416016e-03, -2.62451172e-03, -2.07519531e-03, -2.38037109e-03]
+audio_data = [3.0517571e-05, -8.54492188e-04, -1.09863281e-03, -9.4604492e-04,\
+            -1.31225586e-03, -1.09863281e-03, -1.73950195e-03, -2.1057189e-03,\
+            -2.04467773e-03, -1.46484375e-03, -1.43432617e-03, -9.4604492e-04,\
+            -1.95312500e-03, -1.86157227e-03, -2.10571289e-03, -2.3193354e-03,\
+            -2.01416016e-03, -2.62451172e-03, -2.07519531e-03, -2.3803719e-03]
 audio_data = np.array(audio_data)
 samplerate = 10
 
 class TestAugmentor(unittest.TestCase):
     def test_volume(self):
-        augmentation_config='[{"type": "volume","params": {"min_gain_dBFS": -15, "max_gain_dBFS": 15},"prob": 1.0}]'
-        augmentation_pipeline = AugmentationPipeline(augmentation_config=augmentation_config,
-                                                     random_seed=random_seed)
-        audio_segment = audio.AudioSegment(audio_data, samplerate)
-        augmentation_pipeline.transform_audio(audio_segment)
-        original_audio = audio.AudioSegment(audio_data, samplerate)
-        self.assertFalse(np.any(audio_segment.samples == original_audio.samples))
+        config_json = '[{"type": "volume","params": {"min_gain_dBFS": -15, '\
+        '"max_gain_dBFS": 15},"prob": 1.0}]'
+        aug_pipeline = AugmentationPipeline(augmentation_config=config_json,
+                                            random_seed=random_seed)
+        audio_seg = audio.AudioSegment(audio_data, samplerate)
+        aug_pipeline.transform_audio(audio_seg)
+        orig_audio = audio.AudioSegment(audio_data, samplerate)
+        self.assertFalse(np.any(audio_seg.samples == orig_audio.samples))
 
     def test_speed(self):
-        augmentation_config='[{"type": "speed","params": {"min_speed_rate": 1.2,"max_speed_rate": 1.4},"prob": 1.0}]'
-        augmentation_pipeline = AugmentationPipeline(augmentation_config=augmentation_config,
-                                                     random_seed=random_seed)
-        audio_segment = audio.AudioSegment(audio_data, samplerate)
-        augmentation_pipeline.transform_audio(audio_segment)
-        original_audio = audio.AudioSegment(audio_data, samplerate)
-        self.assertFalse(np.any(audio_segment.samples == original_audio.samples))
+        config_json = '[{"type":"speed","params": {"min_speed_rate": 1.2,' \
+        '"max_speed_rate": 1.4},"prob": 1.0}]'
+        aug_pipeline = AugmentationPipeline(augmentation_config=config_json,
+                                            random_seed=random_seed)
+        audio_seg = audio.AudioSegment(audio_data, samplerate)
+        aug_pipeline.transform_audio(audio_seg)
+        orig_audio = audio.AudioSegment(audio_data, samplerate)
+        self.assertFalse(np.any(audio_seg.samples == orig_audio.samples))
 
     def test_resample(self):
-        augmentation_config='[{"type": "resample","params": {"new_sample_rate":5},"prob": 1.0}]'
-        augmentation_pipeline = AugmentationPipeline(augmentation_config=augmentation_config,
-                                                     random_seed=random_seed)
-        audio_segment = audio.AudioSegment(audio_data, samplerate)
-        augmentation_pipeline.transform_audio(audio_segment)
-        self.assertTrue(audio_segment.sample_rate == 5)
+        config_json = '[{"type":"resample","params": {"new_sample_rate":5},'\
+        '"prob": 1.0}]'
+        aug_pipeline = AugmentationPipeline(augmentation_config=config_json,
+                                            random_seed=random_seed)
+        audio_seg = audio.AudioSegment(audio_data, samplerate)
+        aug_pipeline.transform_audio(audio_seg)
+        self.assertTrue(audio_seg.sample_rate == 5)
 
     def test_bayesial(self):
-        augmentation_config='[{"type": "bayesian_normal","params": {"target_db": -20, "prior_db": -4, "prior_samples": -8, "startup_delay": 0.0},"prob": 1.0}]'
-        augmentation_pipeline = AugmentationPipeline(augmentation_config=augmentation_config,
-                                                     random_seed=random_seed)
-        audio_segment = audio.AudioSegment(audio_data, samplerate)
-        augmentation_pipeline.transform_audio(audio_segment)
-        original_audio = audio.AudioSegment(audio_data, samplerate)
-        self.assertFalse(np.any(audio_segment.samples == original_audio.samples))
+        config_json = '[{"type":"bayesian_normal","params":{"target_db":-20,' \
+        '"prior_db":-4, "prior_samples": -8, "startup_delay": 0.0},"prob":1.0}]'
+        aug_pipeline = AugmentationPipeline(augmentation_config=config_json,
+                                            random_seed=random_seed)
+        audio_seg = audio.AudioSegment(audio_data, samplerate)
+        aug_pipeline.transform_audio(audio_seg)
+        orig_audio = audio.AudioSegment(audio_data, samplerate)
+        self.assertFalse(np.any(audio_seg.samples == orig_audio.samples))
 
 if __name__ == '__main__':
     unittest.main()