diff --git a/data_utils.py b/data_utils.py
index 09f42ac..fdfd287 100644
--- a/data_utils.py
+++ b/data_utils.py
@@ -14,9 +14,8 @@ class TextMelLoader(torch.utils.data.Dataset):
         2) normalizes text and converts them to sequences of one-hot vectors
         3) computes mel-spectrograms from audio files.
     """
-    def __init__(self, audiopaths_and_text, hparams, shuffle=True):
-        self.audiopaths_and_text = load_filepaths_and_text(
-            audiopaths_and_text, hparams.sort_by_length)
+    def __init__(self, audiopaths_and_text, hparams):
+        self.audiopaths_and_text = load_filepaths_and_text(audiopaths_and_text)
         self.text_cleaners = hparams.text_cleaners
         self.max_wav_value = hparams.max_wav_value
         self.sampling_rate = hparams.sampling_rate
@@ -26,8 +25,7 @@ class TextMelLoader(torch.utils.data.Dataset):
             hparams.n_mel_channels, hparams.sampling_rate, hparams.mel_fmin,
             hparams.mel_fmax)
         random.seed(1234)
-        if shuffle:
-            random.shuffle(self.audiopaths_and_text)
+        random.shuffle(self.audiopaths_and_text)
 
     def get_mel_text_pair(self, audiopath_and_text):
         # separate filename and text
@@ -38,7 +36,10 @@ class TextMelLoader(torch.utils.data.Dataset):
 
     def get_mel(self, filename):
         if not self.load_mel_from_disk:
-            audio = load_wav_to_torch(filename, self.sampling_rate)
+            audio, sampling_rate = load_wav_to_torch(filename)
+            if sampling_rate != self.stft.sampling_rate:
+                raise ValueError("{} {} SR doesn't match target {} SR".format(
+                    sampling_rate, self.stft.sampling_rate))
             audio_norm = audio / self.max_wav_value
             audio_norm = audio_norm.unsqueeze(0)
             audio_norm = torch.autograd.Variable(audio_norm, requires_grad=False)
@@ -87,9 +88,9 @@ class TextMelCollate():
             text = batch[ids_sorted_decreasing[i]][0]
             text_padded[i, :text.size(0)] = text
 
-        # Right zero-pad mel-spec with extra single zero vector to mark the end
+        # Right zero-pad mel-spec
         num_mels = batch[0][1].size(0)
-        max_target_len = max([x[1].size(1) for x in batch]) + 1
+        max_target_len = max([x[1].size(1) for x in batch])
         if max_target_len % self.n_frames_per_step != 0:
             max_target_len += self.n_frames_per_step - max_target_len % self.n_frames_per_step
             assert max_target_len % self.n_frames_per_step == 0
@@ -103,7 +104,7 @@ class TextMelCollate():
         for i in range(len(ids_sorted_decreasing)):
             mel = batch[ids_sorted_decreasing[i]][1]
             mel_padded[i, :, :mel.size(1)] = mel
-            gate_padded[i, mel.size(1):] = 1
+            gate_padded[i, mel.size(1)-1:] = 1
             output_lengths[i] = mel.size(1)
 
         return text_padded, input_lengths, mel_padded, gate_padded, \