diff --git a/TTS/tts/layers/vits/discriminator.py b/TTS/tts/layers/vits/discriminator.py
index 148f283c..4aba36df 100644
--- a/TTS/tts/layers/vits/discriminator.py
+++ b/TTS/tts/layers/vits/discriminator.py
@@ -2,7 +2,7 @@ import torch
 from torch import nn
 from torch.nn.modules.conv import Conv1d
 
-from TTS.vocoder.models.hifigan_discriminator import DiscriminatorP, MultiPeriodDiscriminator
+from TTS.vocoder.models.hifigan_discriminator import DiscriminatorP
 
 
 class DiscriminatorS(torch.nn.Module):
@@ -12,19 +12,19 @@ class DiscriminatorS(torch.nn.Module):
         use_spectral_norm (bool): if `True` swith to spectral norm instead of weight norm.
     """
 
-    def __init__(self, use_spectral_norm=False):
+    def __init__(self, use_spectral_norm=False, upsampling_rates=[4, 4, 4, 4]):
         super().__init__()
         norm_f = nn.utils.spectral_norm if use_spectral_norm else nn.utils.weight_norm
-        self.convs = nn.ModuleList(
-            [
-                norm_f(Conv1d(1, 16, 15, 1, padding=7)),
-                norm_f(Conv1d(16, 64, 41, 4, groups=4, padding=20)),
-                norm_f(Conv1d(64, 256, 41, 4, groups=16, padding=20)),
-                norm_f(Conv1d(256, 1024, 41, 4, groups=64, padding=20)),
-                norm_f(Conv1d(1024, 1024, 41, 4, groups=256, padding=20)),
-                norm_f(Conv1d(1024, 1024, 5, 1, padding=2)),
-            ]
-        )
+        self.convs = nn.ModuleList([norm_f(Conv1d(1, 16, 15, 1, padding=7))])
+        groups = 4
+        in_channels = 16
+        out_channels = 64
+        for rate in upsampling_rates:
+            self.convs.append(norm_f(Conv1d(in_channels, out_channels, 41, rate, groups=groups, padding=20)))
+            groups = min(groups * rate, 256)
+            in_channels = min(in_channels * rate, 1024)
+            out_channels = min(out_channels * rate, 1024)
+        self.convs += [norm_f(Conv1d(1024, 1024, 5, 1, padding=2))]
         self.conv_post = norm_f(Conv1d(1024, 1, 3, 1, padding=1))
 
     def forward(self, x):
@@ -58,10 +58,10 @@ class VitsDiscriminator(nn.Module):
         use_spectral_norm (bool): if `True` swith to spectral norm instead of weight norm.
     """
 
-    def __init__(self, periods=(2, 3, 5, 7, 11), use_spectral_norm=False):
+    def __init__(self, use_spectral_norm=False, periods=[2, 3, 5, 7, 11], upsampling_rates=[4,4,4,4]):
         super().__init__()
         self.nets = nn.ModuleList()
-        self.nets.append(DiscriminatorS(use_spectral_norm=use_spectral_norm))
+        self.nets.append(DiscriminatorS(use_spectral_norm=use_spectral_norm, upsampling_rates=upsampling_rates))
         self.nets.extend([DiscriminatorP(i, use_spectral_norm=use_spectral_norm) for i in periods])
 
     def forward(self, x, x_hat=None):