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diff --git a/power_sequencer/operators/audiosync/mfcc/trfbank.py b/power_sequencer/operators/audiosync/mfcc/trfbank.py
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+++ b/power_sequencer/operators/audiosync/mfcc/trfbank.py
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+#
+# Copyright (C) 2016-2019 by Nathan Lovato, Daniel Oakey, Razvan Radulescu, and contributors
+#
+# This file is part of Power Sequencer.
+#
+# Power Sequencer is free software: you can redistribute it and/or modify it under the terms of the
+# GNU General Public License as published by the Free Software Foundation, either version 3 of the
+# License, or (at your option) any later version.
+#
+# Power Sequencer is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY;
+# without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License along with Power Sequencer. If
+# not, see <https://www.gnu.org/licenses/>.
+#
+import numpy as np
+
+
+def trfbank(fs, nfft, lowfreq, linsc, logsc, nlinfilt, nlogfilt):
+    """Compute triangular filterbank for MFCC computation."""
+    # Total number of filters
+    nfilt = nlinfilt + nlogfilt
+
+    # ------------------------
+    # Compute the filter bank
+    # ------------------------
+    # Compute start/middle/end points of the triangular filters in spectral
+    # domain
+    freqs = np.zeros(nfilt + 2)
+    freqs[:nlinfilt] = lowfreq + np.arange(nlinfilt) * linsc
+    freqs[nlinfilt:] = freqs[nlinfilt - 1] * logsc ** np.arange(1, nlogfilt + 3)
+    heights = 2.0 / (freqs[2:] - freqs[0:-2])
+
+    # Compute filterbank coeff (in fft domain, in bins)
+    fbank = np.zeros((nfilt, nfft))
+    # FFT bins (in Hz)
+    nfreqs = np.arange(nfft) / (1.0 * nfft) * fs
+    for i in range(nfilt):
+        low = freqs[i]
+        cen = freqs[i + 1]
+        hi = freqs[i + 2]
+
+        lid = np.arange(np.floor(low * nfft / fs) + 1, np.floor(cen * nfft / fs) + 1, dtype=np.int)
+        lslope = heights[i] / (cen - low)
+        rid = np.arange(np.floor(cen * nfft / fs) + 1, np.floor(hi * nfft / fs) + 1, dtype=np.int)
+        rslope = heights[i] / (hi - cen)
+        fbank[i][lid] = lslope * (nfreqs[lid] - low)
+        fbank[i][rid] = rslope * (hi - nfreqs[rid])
+
+    return fbank, freqs