[+] Runtime testing

2022-04-04 19:49:05 -04:00
parent 3a83aa9a11
commit 33fada11c3
2 changed files with 330 additions and 0 deletions
@@ -0,0 +1,101 @@
+import librosa as librosa
+import numpy as np
+import parselmouth
+import torchaudio
+from inaSpeechSegmenter import Segmenter
+from inaSpeechSegmenter.features import to_wav, _wav2feats
+from inaSpeechSegmenter.sidekit_mfcc import read_wav
+
+from server.utils import Timer
+
+np.seterr(invalid='ignore')
+
+if __name__ == '__main__':
+    f = '/workspace/EECS 6414/voice_cnn/VT 150hz baseline example.mp3'
+    timer = Timer()
+
+    seg = Segmenter()
+    seg('/workspace/EECS 6414/voice_cnn/test.wav')
+    timer.log('ML engine loaded (One time expense, not counted in running time).')
+
+    print()
+
+    fp = f
+    fp = str(to_wav(f).absolute())
+    timer.log('FFMPEG Convert file to WAV 16000Hz')
+    fp = str(to_wav(f, sr=None).absolute())
+    timer.log('FFMPEG Convert file to WAV (original sr kept)')
+
+    print()
+
+    # Read file
+    parselmouth.Sound(fp)
+    timer.log('Parselmouth: Read file.')
+    sound = parselmouth.Sound(fp)
+    timer.log('Parselmouth: Read file.')
+
+    # librosa.load(fp)
+    # timer.log('Librosa: Read file')
+    # librosa.load(fp)
+    # timer.log('Librosa: Read file')
+
+    read_wav(fp)
+    timer.log('Read file with read_wav')
+    y, sr, _ = read_wav(fp)
+    timer.log(f'Read file with read_wav (decoded sr = {sr})')
+
+    torchaudio.load(fp)
+    timer.log('Read file with torchaudio')
+    torchaudio.load(fp)
+    timer.log('Read file with torchaudio')
+
+    print()
+
+    # Calculate features
+    pitch = sound.to_pitch(0.01)
+    timer.log('Parselmouth: Pitch calculated (0.01)')
+    sound.to_pitch(0.01)
+    timer.log('Parselmouth: Pitch calculated again (0.01)')
+    sound.to_pitch(0.032)
+    timer.log('Parselmouth: Pitch calculated again (0.032)')
+
+    print()
+
+    sound.to_formant_burg(0.01)
+    timer.log('Parselmouth: Formant calculated (0.01)')
+    sound.to_formant_burg(0.01)
+    timer.log('Parselmouth: Formant calculated again (0.01)')
+    sound.to_formant_burg(0.032)
+    timer.log('Parselmouth: Formant calculated again (0.032)')
+
+    print()
+
+    sound.to_spectrogram(window_length=0.128, time_step=0.032)
+    timer.log('Parselmouth: Spectrogram calculated (n_fft=0.128, step=0.032)')
+
+    print()
+
+    librosa.core.piptrack(y=y, sr=sr)
+    timer.log('Librosa: piptrack')
+    spec = np.abs(librosa.stft(y, n_fft=1024, hop_length=512))
+    timer.log('Librosa: STFT')
+    mel_spect = librosa.feature.melspectrogram(y=y, sr=sr, n_fft=2048, hop_length=512, htk=True)
+    timer.log('Librosa: Mel spectrogram')
+
+    print()
+
+    _wav2feats(fp)
+    timer.log('ML: Calculate mspect feats')
+    mspect, loge, diff_len = _wav2feats(fp)
+    timer.log('ML: Calculate mspect feats')
+
+    seg.segment_feats(mspect, loge, diff_len, 0)
+    timer.log('ML: Segment feats')
+    seg.segment_feats(mspect, loge, diff_len, 0)
+    timer.log('ML: Segment feats')
+
+    # Calculate ML
+    # seg(f)
+    # timer.log('ML Segmented')
+    # seg(f)
+    # timer.log('ML Segmented again')