implemented pitch plotting

speech_pitch.py

@@ -1,5 +1,9 @@
 import parselmouth as pm
 from pysndfile import sndio as snd
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+sns.set() # Use seaborn's default style to make graphs more pretty
 
 def pitch_array(sample_file='outputs/audio/sunflowers-Victoria-180-normal-870.aiff'):
     samples, samplerate, _  = snd.read(sample_file)
@@ -23,24 +27,110 @@ def compute_mfcc(sample_file='outputs/audio/sunflowers-Victoria-180-normal-870.a
     # sample_mfcc.to_array().shape
     return sample_mfcc.to_array()
 
+def compute_formants(sample_file='outputs/audio/sunflowers-Victoria-180-normal-870.aiff'):
+    sample_file='outputs/audio/sunflowers-Victoria-180-normal-870.aiff'
+    samples, samplerate, _  = snd.read(sample_file)
+    sample_sound = pm.Sound(values=samples,sampling_frequency=samplerate)
+    sample_formant = sample_sound.to_formant_burg()
+    sample_formant.x_bins()
+    # sample_mfcc.to_array().shape
+    return sample_mfcc.to_array()
+
+def draw_spectrogram(spectrogram, dynamic_range=70):
+    X, Y = spectrogram.x_grid(), spectrogram.y_grid()
+    sg_db = 10 * np.log10(spectrogram.values.T)
+    plt.pcolormesh(X, Y, sg_db, vmin=sg_db.max() - dynamic_range, cmap='afmhot')
+    plt.ylim([spectrogram.ymin, spectrogram.ymax])
+    plt.xlabel("time [s]")
+    plt.ylabel("frequency [Hz]")
+
+def draw_intensity(intensity):
+    plt.plot(intensity.xs(), intensity.values, linewidth=3, color='w')
+    plt.plot(intensity.xs(), intensity.values, linewidth=1)
+    plt.grid(False)
+    plt.ylim(0)
+    plt.ylabel("intensity [dB]")
+
+def draw_pitch(pitch):
+    # Extract selected pitch contour, and
+    # replace unvoiced samples by NaN to not plot
+    pitch_values = pitch.to_matrix().values
+    pitch_values[pitch_values==0] = np.nan
+    plt.plot(pitch.xs(), pitch_values, linewidth=3, color='w')
+    plt.plot(pitch.xs(), pitch_values, linewidth=1)
+    plt.grid(False)
+    plt.ylim(0, pitch.ceiling)
+    plt.ylabel("pitch [Hz]")
+
+def pm_snd(sample_file):
+    # sample_file = 'inputs/self-apple/apple-low1.aiff'
+    samples, samplerate, _  = snd.read(sample_file)
+    return pm.Sound(values=samples,sampling_frequency=samplerate)
+def plot_sample_raw(sample_file='outputs/audio/sunflowers-Victoria-180-normal-870.aiff'):
+    # %matplotlib inline
+    # sample_file='outputs/audio/sunflowers-Victoria-180-normal-870.aiff
+    snd_d = pm_snd(sample_file)
+    plt.figure()
+    plt.plot(snd_d.xs(), snd_d.values)
+    plt.xlim([snd_d.xmin, snd_d.xmax])
+    plt.xlabel("time [s]")
+    plt.ylabel("amplitude")
+    plt.show()
+
+def plot_sample_intensity(sample_file='outputs/audio/sunflowers-Victoria-180-normal-870.aiff'):
+    snd_d = pm_snd(sample_file)
+    intensity = snd_d.to_intensity()
+    spectrogram = snd_d.to_spectrogram()
+    plt.figure()
+    draw_spectrogram(spectrogram)
+    plt.twinx()
+    draw_intensity(intensity)
+    plt.xlim([snd_d.xmin, snd_d.xmax])
+    plt.show()
+
+def plot_sample_pitch(sample_file='outputs/audio/sunflowers-Victoria-180-normal-870.aiff'):
+    snd_d = pm_snd(sample_file)
+    pitch = snd_d.to_pitch()
+    spectrogram = snd_d.to_spectrogram(window_length=0.03, maximum_frequency=8000)
+    plt.figure()
+    draw_spectrogram(spectrogram)
+    plt.twinx()
+    draw_pitch(pitch)
+    plt.xlim([snd_d.xmin, snd_d.xmax])
+    plt.show()
+
+    # snd_part = snd_d.extract_part(from_time=0.9, preserve_times=True)
+    # plt.figure()
+    # plt.plot(snd_part.xs(), snd_part.values, linewidth=0.5)
+    # plt.xlim([snd_part.xmin, snd_part.xmax])
+    # plt.xlabel("time [s]")
+    # plt.ylabel("amplitude")
+    # plt.show()
+
+
+if __name__ == '__main__':
     # sunflowers_vic_180_norm = pitch_array('outputs/audio/sunflowers-Victoria-180-normal-870.aiff')
     # sunflowers_fred_180_norm = pitch_array('outputs/audio/sunflowers-Fred-180-normal-6515.aiff')
     # sunflowers_vic_180_norm_mfcc = compute_mfcc('outputs/audio/sunflowers-Victoria-180-normal-870.aiff')
-fred_180_norm_mfcc = compute_mfcc('outputs/audio/sunflowers-Fred-180-normal-6515.aiff')
+    # fred_180_norm_mfcc = compute_mfcc('outputs/audio/sunflowers-Fred-180-normal-6515.aiff')
-alex_mfcc = compute_mfcc('outputs/audio/sunflowers-Alex-180-normal-4763.aiff')
+    # alex_mfcc = compute_mfcc('outputs/audio/sunflowers-Alex-180-normal-4763.aiff')
-# # sunflowers_vic_180_norm.shape
+    # # # sunflowers_vic_180_norm.shape
-# # sunflowers_fred_180_norm.shape
+    # # # sunflowers_fred_180_norm.shape
+    # # alex_mfcc.shape
+    # # sunflowers_vic_180_norm_mfcc.shape
+    # # sunflowers_fred_180_norm_mfcc.shape
+    # from speech_spectrum import generate_aiff_spectrogram
+    # vic_spec = generate_aiff_spectrogram('outputs/audio/sunflowers-Victoria-180-normal-870.aiff')
+    # alex_spec = generate_aiff_spectrogram('outputs/audio/sunflowers-Alex-180-normal-4763.aiff')
+    # alex150spec = generate_aiff_spectrogram('outputs/audio/sunflowers-Alex-150-normal-589.aiff')
+    # vic_spec.shape
+    # alex_spec.shape
+    # alex150spec.shape
     # alex_mfcc.shape
-# sunflowers_vic_180_norm_mfcc.shape
+    # fred_180_norm_mfcc.shape
-# sunflowers_fred_180_norm_mfcc.shape
+    plot_sample_pitch('outputs/audio/sunflowers-Victoria-180-normal-870.aiff')
-from speech_spectrum import generate_aiff_spectrogram
+    plot_sample_pitch('inputs/self-apple/apple-low1.aiff')
-vic_spec = generate_aiff_spectrogram('outputs/audio/sunflowers-Victoria-180-normal-870.aiff')
+    plot_sample_pitch('inputs/self-apple/apple-low2.aiff')
-alex_spec = generate_aiff_spectrogram('outputs/audio/sunflowers-Alex-180-normal-4763.aiff')
+    plot_sample_pitch('inputs/self-apple/apple-medium1.aiff')
-alex150spec = generate_aiff_spectrogram('outputs/audio/sunflowers-Alex-150-normal-589.aiff')
-vic_spec.shape
-alex_spec.shape
-alex150spec.shape
-alex_mfcc.shape
-fred_180_norm_mfcc.shape
     # pm.SoundFileFormat
     # pm.Pitch.get_number_of_frames()