expose parameters

diffsptk/core/istft.py

@@ -35,6 +35,10 @@ class InverseShortTermFourierTransform(nn.Module):
     fft_length : int >= L [scalar]
         Number of FFT bins, :math:`N`.
 
+    center : bool [scalar]
+        If True, assume that the center of data is the center of frame, otherwise
+        assume that the center of data is the left edge of frame.
+
     norm : ['none', 'power', 'magnitude']
         Normalization type of window.
 
@@ -49,6 +53,8 @@ def __init__(
         frame_length,
         frame_period,
         fft_length,
+        *,
+        center=True,
         norm="power",
         window="blackman",
     ):
@@ -57,7 +63,9 @@ def __init__(
         self.ifft = Lambda(
             lambda x: torch.fft.irfft(x, n=fft_length)[..., :frame_length]
         )
-        self.unframe = Unframe(frame_length, frame_period, norm=norm, window=window)
+        self.unframe = Unframe(
+            frame_length, frame_period, center=center, norm=norm, window=window
+        )
 
     def forward(self, y, out_length=None):
         """Compute inverse short-term Fourier transform.

diffsptk/core/mglsadf.py

@@ -364,10 +364,13 @@ def __init__(
         phase="minimum",
         frame_length=400,
         fft_length=512,
-        **kwargs,
+        n_fft=512,
+        **stft_kwargs,
     ):
         super(FrequencyDomainFIRFilter, self).__init__()
 
+        assert 2 * frame_period < frame_length
+
         self.ignore_gain = ignore_gain
 
         if self.ignore_gain:
@@ -380,17 +383,18 @@ def __init__(
             )
 
         self.stft = ShortTermFourierTransform(
-            frame_length, frame_period, fft_length, out_format="complex", **kwargs
+            frame_length, frame_period, fft_length, out_format="complex", **stft_kwargs
         )
         self.istft = InverseShortTermFourierTransform(
-            frame_length, frame_period, fft_length, **kwargs
+            frame_length, frame_period, fft_length, **stft_kwargs
         )
         self.mgc2sp = MelGeneralizedCepstrumToSpectrum(
             filter_order,
             fft_length,
             alpha=alpha,
             gamma=gamma,
             out_format="magnitude" if phase == "zero" else "complex",
+            n_fft=n_fft,
         )
 
     def forward(self, x, mc):

diffsptk/core/stft.py

@@ -37,6 +37,10 @@ class ShortTermFourierTransform(nn.Module):
     fft_length : int >= L [scalar]
         Number of FFT bins, :math:`N`.
 
+    center : bool [scalar]
+        If True, assume that the center of data is the center of frame, otherwise
+        assume that the center of data is the left edge of frame.
+
     zmean : bool [scalar]
         If True, perform mean subtraction on each frame.
 
@@ -63,6 +67,8 @@ def __init__(
         frame_length,
         frame_period,
         fft_length,
+        *,
+        center=True,
         zmean=False,
         norm="power",
         window="blackman",
@@ -73,7 +79,7 @@ def __init__(
         super(ShortTermFourierTransform, self).__init__()
 
         self.stft = nn.Sequential(
-            Frame(frame_length, frame_period, zmean=zmean),
+            Frame(frame_length, frame_period, center=center, zmean=zmean),
             Window(frame_length, fft_length, norm=norm, window=window),
             Lambda(torch.fft.rfft)
             if out_format == "complex"