|
import numpy as np |
|
from fairseq.data.audio.feature_transforms import ( |
|
AudioFeatureTransform, |
|
register_audio_feature_transform, |
|
) |
|
|
|
|
|
@register_audio_feature_transform("global_cmvn") |
|
class GlobalCMVN(AudioFeatureTransform): |
|
"""Global CMVN (cepstral mean and variance normalization). The global mean |
|
and variance need to be pre-computed and stored in NumPy format (.npz).""" |
|
|
|
@classmethod |
|
def from_config_dict(cls, config=None): |
|
_config = {} if config is None else config |
|
return GlobalCMVN(_config.get("stats_npz_path")) |
|
|
|
def __init__(self, stats_npz_path): |
|
self.stats_npz_path = stats_npz_path |
|
stats = np.load(stats_npz_path) |
|
self.mean, self.std = stats["mean"], stats["std"] |
|
|
|
def __repr__(self): |
|
return self.__class__.__name__ + f'(stats_npz_path="{self.stats_npz_path}")' |
|
|
|
def __call__(self, x): |
|
x = np.subtract(x, self.mean) |
|
x = np.divide(x, self.std) |
|
return x |
|
|
