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- import numpy as np
-
- SEGMENT_LENGTH_TRAIN = 16000
-
-
- def to_segment(batch, segment_length=SEGMENT_LENGTH_TRAIN):
- """
- Dataset mapping function to split one audio into segments.
- It only works in batch mode.
- """
- noisy_arrays = []
- for x in batch['noisy']:
- length = len(x['array'])
- noisy = np.array(x['array'])
- for offset in range(segment_length, length, segment_length):
- noisy_arrays.append(noisy[offset - segment_length:offset])
- clean_arrays = []
- for x in batch['clean']:
- length = len(x['array'])
- clean = np.array(x['array'])
- for offset in range(segment_length, length, segment_length):
- clean_arrays.append(clean[offset - segment_length:offset])
- return {'noisy': noisy_arrays, 'clean': clean_arrays}
-
-
- def audio_norm(x):
- rms = (x**2).mean()**0.5
- scalar = 10**(-25 / 20) / rms
- x = x * scalar
- pow_x = x**2
- avg_pow_x = pow_x.mean()
- rmsx = pow_x[pow_x > avg_pow_x].mean()**0.5
- scalarx = 10**(-25 / 20) / rmsx
- x = x * scalarx
- return x
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