def test_batch_pitch(self):
waveform, sample_rate = torchaudio.load(self.test_filepath)
# Single then transform then batch
expected = F.detect_pitch_frequency(waveform, sample_rate)
expected = expected.unsqueeze(0).repeat(3, 1, 1)
# Batch then transform
waveform = waveform.unsqueeze(0).repeat(3, 1, 1)
computed = F.detect_pitch_frequency(waveform, sample_rate)
self.assertTrue(computed.shape == expected.shape,
(computed.shape, expected.shape))
self.assertTrue(torch.allclose(computed, expected))
def test_detect_pitch_frequency_pitch(self, frequency):
sample_rate = 44100
test_sine_waveform = get_sinusoid(frequency=frequency,
sample_rate=sample_rate,
duration=5)
freq = F.detect_pitch_frequency(test_sine_waveform, sample_rate)
threshold = 1
s = ((freq - frequency).abs() > threshold).sum()
self.assertFalse(s)
dct_type=2,
norm='ortho')
plot_spectrogram(mfcc_librosa)
mse = torch.square(mfcc - mfcc_librosa).mean().item()
print('Mean Square Difference: ', mse)
######################################################################
# Pitch
# -----
#
waveform, sample_rate = get_speech_sample()
pitch = F.detect_pitch_frequency(waveform, sample_rate)
plot_pitch(waveform, sample_rate, pitch)
play_audio(waveform, sample_rate)
######################################################################
# Kaldi Pitch (beta)
# ------------------
#
# Kaldi Pitch feature [1] is a pitch detection mechanism tuned for automatic
# speech recognition (ASR) applications. This is a beta feature in ``torchaudio``,
# and it is available only in ``functional``.
#
# 1. A pitch extraction algorithm tuned for automatic speech recognition
#
# Ghahremani, B. BabaAli, D. Povey, K. Riedhammer, J. Trmal and S.
# Khudanpur
def func(tensor):
sample_rate = 44100
return F.detect_pitch_frequency(tensor, sample_rate)
