Duum · February 22, 2016 06:39 · Aug 6, 2012
diff --git a/gistfile1.py b/gistfile1.py
@@ -0,0 +1,53 @@
+import numpy as np
+
+
+def freq2mel(freq):
+    return 1127.01048 * np.log(1 + freq / 700.0)
+
+def mel2freq(mel):
+    return (np.exp(mel / 1127.01048) - 1) * 700
+
+def mel_binning_matrix(specgram_window_size, sample_frequency, num_mel_bands):
+    """
+    function that returns a matrix that converts a regular DFT to a mel-spaced DFT,
+    by binning coefficients.
+    
+    specgram_window_size: the window length used to compute the spectrograms
+    sample_frequency: the sample frequency of the input audio
+    num_mel_bands: the number of desired mel bands.
+    
+    The output is a matrix with dimensions (specgram_window_size/2 + 1, num_bands)
+    """
+    min_freq, max_freq = 0, sample_frequency / 2
+    min_mel = freq2mel(min_freq)
+    max_mel = freq2mel(max_freq)
+    num_specgram_components = specgram_window_size / 2 + 1
+    m = np.zeros((num_specgram_components, num_mel_bands))
+
+    r = np.arange(num_mel_bands + 2) # there are (num_mel_bands + 2) filter boundaries / centers
+
+    # evenly spaced filter boundaries in the mel domain:
+    mel_filter_boundaries = r * (max_mel - min_mel) / (num_mel_bands + 1) + min_mel
+
+    def coeff(idx, mel): # gets the unnormalised filter coefficient of filter 'idx' for a given mel value.
+        lo, cen, hi = mel_filter_boundaries[idx:idx+3]
+        if mel <= lo or mel >= hi:
+            return 0
+        # linearly interpolate
+        if lo <= mel <= cen:
+            return (mel - lo) / (cen - lo)
+        elif cen <= mel <= hi:
+            return 1 - (mel - cen) / (hi - cen)
+
+
+    for k in xrange(num_specgram_components):
+        # compute mel representation of the given specgram component idx
+        freq = k / float(num_specgram_components) * (sample_frequency / 2)
+        mel = freq2mel(freq)
+        for i in xrange(num_mel_bands):
+            m[k, i] = coeff(i, mel)
+
+    # normalise so that each filter has unit contribution
+    return m / m.sum(0)
+
+
No results found