diff --git a/_paramters.py b/_paramters.py
index b4ee88f..83d2b4e 100644
--- a/_paramters.py
+++ b/_paramters.py
@@ -33,8 +33,9 @@ main_arg_parser.add_argument("--data_loudness_ratio", type=float, default=0, hel
 main_arg_parser.add_argument("--data_shift_ratio", type=float, default=0.3, help="")  # 0.3
 main_arg_parser.add_argument("--data_noise_ratio", type=float, default=0, help="")  # 0.4
 main_arg_parser.add_argument("--data_mask_ratio", type=float, default=0, help="")  # 0.2
-main_arg_parser.add_argument("--data_speed_ratio", type=float, default=0, help="")  # 0.3
-main_arg_parser.add_argument("--data_speed_factor", type=float, default=0, help="")  # 0.7
+main_arg_parser.add_argument("--data_speed_amount", type=float, default=0, help="")  # 0.3
+main_arg_parser.add_argument("--data_speed_min", type=float, default=0, help="")  # 0.7
+main_arg_parser.add_argument("--data_speed_max", type=float, default=0, help="")  # 1.7
 
 # Model Parameters
 main_arg_parser.add_argument("--model_type", type=str, default="RCC", help="")
diff --git a/util/module_mixins.py b/util/module_mixins.py
index 0f786d0..d9ce58f 100644
--- a/util/module_mixins.py
+++ b/util/module_mixins.py
@@ -113,17 +113,25 @@ class BinaryMaskDatasetMixin:
         # Dataset
         # =============================================================================
         # Mel Transforms
-        mel_transforms_train = Compose([
-            # Audio to Mel Transformations
-            Speed(speed_factor=self.params.speed_factor, max_ratio=self.params.speed_ratio),
-            AudioToMel(sr=self.params.sr, n_mels=self.params.n_mels, n_fft=self.params.n_fft,
-                       hop_length=self.params.hop_length),
-            MelToImage()])
         mel_transforms = Compose([
             # Audio to Mel Transformations
-            AudioToMel(sr=self.params.sr, n_mels=self.params.n_mels, n_fft=self.params.n_fft,
+            AudioToMel(sr=self.params.sr,
+                       n_mels=self.params.n_mels,
+                       n_fft=self.params.n_fft,
                        hop_length=self.params.hop_length),
             MelToImage()])
+
+        mel_transforms_train = Compose([
+            # Audio to Mel Transformations
+            Speed(max_amount=self.params.speed_amount,
+                  speed_min=self.params.speed_min,
+                  speed_max=self.params.speed_max
+                  ),
+            mel_transforms])
+
+        # Utility
+        util_transforms = Compose([NormalizeLocal(), ToTensor()])
+
         # Data Augmentations
         aug_transforms = Compose([
             RandomApply([
@@ -132,11 +140,7 @@ class BinaryMaskDatasetMixin:
                 ShiftTime(self.params.shift_ratio),
                 MaskAug(self.params.mask_ratio),
                 ], p=0.6),
-            # Utility
-            NormalizeLocal(),
-            ToTensor()
-        ])
-        val_transforms = Compose([NormalizeLocal(), ToTensor()])
+            util_transforms])
 
         # Datasets
         from datasets.binar_masks import BinaryMasksDataset
@@ -149,12 +153,12 @@ class BinaryMaskDatasetMixin:
                                                  mel_transforms=mel_transforms_train, transforms=aug_transforms),
                 # VALIDATION DATASET
                 val_train_dataset=BinaryMasksDataset(self.params.root, setting=V.DATA_OPTIONS.train,
-                                                     mel_transforms=mel_transforms, transforms=val_transforms),
+                                                     mel_transforms=mel_transforms, transforms=util_transforms),
                 val_dataset=BinaryMasksDataset(self.params.root, setting=V.DATA_OPTIONS.devel,
-                                               mel_transforms=mel_transforms, transforms=val_transforms),
+                                               mel_transforms=mel_transforms, transforms=util_transforms),
                 # TEST DATASET
                 test_dataset=BinaryMasksDataset(self.params.root, setting=V.DATA_OPTIONS.test,
-                                                mel_transforms=mel_transforms, transforms=val_transforms),
+                                                mel_transforms=mel_transforms, transforms=util_transforms),
             )
         )
         return dataset