3 files changed, 6 insertions, 6 deletions
diff --git a/alc/effects/convolution.cpp b/alc/effects/convolution.cpp
index 2a0a0fad..ee7b9e8f 100644
--- a/alc/effects/convolution.cpp
+++ b/alc/effects/convolution.cpp
@@ -298,7 +298,7 @@ void ConvolutionState::setBuffer(const ALCdevice *device, const BufferStorage *b
             done += todo;
             std::fill(iter, fftbuffer->end(), complex_d{});
 
-            complex_fft(*fftbuffer, -1.0);
+            forward_fft(*fftbuffer);
             filteriter = std::copy_n(fftbuffer->cbegin(), m, filteriter);
         }
     }
@@ -418,7 +418,7 @@ void ConvolutionState::process(const size_t samplesToDo,
          * frequency bins to the FFT history.
          */
         std::copy_n(mInput.cbegin(), ConvolveUpdateSamples, mFftBuffer.begin());
-        complex_fft(mFftBuffer, -1.0);
+        forward_fft(mFftBuffer);
 
         std::copy_n(mFftBuffer.begin(), m, &mComplexData[curseg*m]);
         mFftBuffer.fill(complex_d{});
@@ -453,7 +453,7 @@ void ConvolutionState::process(const size_t samplesToDo,
              * second-half samples (and this output's second half is
              * subsequently saved for next time).
              */
-            complex_fft(mFftBuffer, 1.0);
+            inverse_fft(mFftBuffer);
 
             /* The iFFT'd response is scaled up by the number of bins, so apply
              * the inverse to normalize the output.
diff --git a/alc/effects/pshifter.cpp b/alc/effects/pshifter.cpp
index 01d24333..d923e376 100644
--- a/alc/effects/pshifter.cpp
+++ b/alc/effects/pshifter.cpp
@@ -169,7 +169,7 @@ void PshifterState::process(const size_t samplesToDo, const al::span<const Float
          */
         for(size_t k{0u};k < STFT_SIZE;k++)
             mFftBuffer[k] = mFIFO[k] * HannWindow[k];
-        complex_fft(mFftBuffer, -1.0);
+        forward_fft(mFftBuffer);
 
         /* Analyze the obtained data. Since the real FFT is symmetric, only
          * STFT_HALF_SIZE+1 samples are needed.
@@ -232,7 +232,7 @@ void PshifterState::process(const size_t samplesToDo, const al::span<const Float
         /* Apply an inverse FFT to get the time-domain siganl, and accumulate
          * for the output with windowing.
          */
-        complex_fft(mFftBuffer, 1.0);
+        inverse_fft(mFftBuffer);
         for(size_t k{0u};k < STFT_SIZE;k++)
             mOutputAccum[k] += HannWindow[k]*mFftBuffer[k].real() * (2.0/STFT_SIZE/OVERSAMP);
 
diff --git a/alc/uhjfilter.cpp b/alc/uhjfilter.cpp
index 9c0692c4..522b6bb7 100644
--- a/alc/uhjfilter.cpp
+++ b/alc/uhjfilter.cpp
@@ -59,7 +59,7 @@ std::array<float,Uhj2Encoder::sFilterSize> GenerateFilter()
     fftBuffer[half_size] = c0;
     for(size_t i{half_size+1};i < fft_size;++i)
         fftBuffer[i] = std::conj(fftBuffer[fft_size - i]);
-    complex_fft(fftBuffer, 1.0);
+    inverse_fft(fftBuffer);
 
     /* Reverse and truncate the filter to a usable size, and store only the
      * non-0 terms. Should this be windowed?