diff --git a/enhancer/utils/transforms.py b/enhancer/utils/transforms.py
index acfc323..fbdb8f9 100644
--- a/enhancer/utils/transforms.py
+++ b/enhancer/utils/transforms.py
@@ -18,15 +18,16 @@ class ConvFFT(nn.Module):
         self.window_len = window_len
         self.nfft = nfft if nfft else np.int(2 ** np.ceil(np.log2(window_len)))
         self.window = torch.from_numpy(
-            get_window(window, window_len).astype("float32")
+            get_window(window, window_len, fftbins=True).astype("float32")
         )
 
-    @property
-    def init_kernel(self):
+    def init_kernel(self, inverse=False):
 
         fourier_basis = np.fft.rfft(np.eye(self.nfft))[: self.window_len]
         real, imag = np.real(fourier_basis), np.imag(fourier_basis)
         kernel = np.concatenate([real, imag], 1).T
+        if inverse:
+            kernel = np.linalg.pinv(kernel).T
         kernel = torch.from_numpy(kernel.astype("float32")).unsqueeze(1)
         kernel *= self.window
         return kernel
@@ -42,7 +43,7 @@ class ConvSTFT(ConvFFT):
     ):
         super().__init__(window_len=window_len, nfft=nfft, window=window)
         self.hop_size = hop_size if hop_size else window_len // 2
-        self.register_buffer("weight", self.init_kernel)
+        self.register_buffer("weight", self.init_kernel())
 
     def forward(self, input):
 
@@ -73,7 +74,7 @@ class ConviSTFT(ConvFFT):
     ):
         super().__init__(window_len=window_len, nfft=nfft, window=window)
         self.hop_size = hop_size if hop_size else window_len // 2
-        self.register_buffer("weight", self.init_kernel)
+        self.register_buffer("weight", self.init_kernel(True))
         self.register_buffer("enframe", torch.eye(window_len).unsqueeze(1))
 
     def forward(self, input, phase=None):
@@ -85,7 +86,7 @@ class ConviSTFT(ConvFFT):
         out = F.conv_transpose1d(input, self.weight, stride=self.hop_size)
         coeff = self.window.unsqueeze(1).repeat(1, 1, input.size(-1)) ** 2
         coeff = F.conv_transpose1d(coeff, self.enframe, stride=self.hop_size)
-        out = out / coeff
+        out = out / (coeff + 1e-8)
         pad = self.window_len - self.hop_size
         out = out[..., pad:-pad]
         return out