requirements.txt updated @torch1.4

speed augmentation updated
paramters updated

audio_toolset/audio_augmentation.py

@@ -9,18 +9,19 @@ import numpy as np
 
 class Speed(object):
 
-    def __init__(self, max_ratio=0.3, speed_factor=1):
-        self.speed_factor = speed_factor
-        self.max_ratio = max_ratio
+    def __init__(self, max_amount=0.3, speed_min=1, speed_max=1):
+        self.speed_max = speed_max
+        self.speed_min = speed_min
+        self.max_amount = max_amount
 
     def __call__(self, x):
-        if not all([self.speed_factor, self.max_ratio]):
-            return x
-        start = int(np.random.randint(0, x.shape[-1],1))
-        end = int((np.random.uniform(0, self.max_ratio, 1) * x.shape[-1]) + start)
+        assert all([self.speed_min, self.speed_max, self.max_amount])
+        start = int(np.random.randint(low=0, high=x.shape[-1], size=1))
+        width = np.random.uniform(low=0, high=self.max_amount, size=1) * x.shape[-1]
+        end = int(width + start)
         end = min(end, x.shape[-1])
         try:
-            speed_factor = float(np.random.uniform(min(self.speed_factor, 1), max(self.speed_factor, 1), 1))
+            speed_factor = float(np.random.uniform(low=self.speed_min, high=self.speed_max, size=1))
             aug_data = librosa.effects.time_stretch(x[start:end], speed_factor)
             return np.concatenate((x[:start], aug_data, x[end:]), axis=0)[:x.shape[-1]]
         except ValueError: