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73 lines
2.2 KiB
73 lines
2.2 KiB
import paddle
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from paddle import nn
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from paddlespeech.audio.compliance import kaldi
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from paddlespeech.s2t.utils.log import Log
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logger = Log(__name__).getlog()
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__all__ = ['KaldiFbank']
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class KaldiFbank(nn.Layer):
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def __init__(
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self,
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fs=16000,
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n_mels=80,
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n_shift=160, # unit:sample, 10ms
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win_length=400, # unit:sample, 25ms
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energy_floor=0.0,
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dither=0.0):
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"""
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Args:
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fs (int): sample rate of the audio
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n_mels (int): number of mel filter banks
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n_shift (int): number of points in a frame shift
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win_length (int): number of points in a frame windows
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energy_floor (float): Floor on energy in Spectrogram computation (absolute)
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dither (float): Dithering constant. Default 0.0
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"""
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super().__init__()
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self.fs = fs
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self.n_mels = n_mels
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num_point_ms = fs / 1000
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self.n_frame_length = win_length / num_point_ms
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self.n_frame_shift = n_shift / num_point_ms
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self.energy_floor = energy_floor
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self.dither = dither
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def __repr__(self):
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return (
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"{name}(fs={fs}, n_mels={n_mels}, "
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"n_frame_shift={n_frame_shift}, n_frame_length={n_frame_length}, "
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"dither={dither}))".format(
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name=self.__class__.__name__,
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fs=self.fs,
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n_mels=self.n_mels,
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n_frame_shift=self.n_frame_shift,
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n_frame_length=self.n_frame_length,
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dither=self.dither, ))
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def forward(self, x: paddle.Tensor):
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"""
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Args:
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x (paddle.Tensor): shape (Ti).
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Not support: [Time, Channel] and Batch mode.
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Returns:
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paddle.Tensor: (T, D)
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"""
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assert x.ndim == 1
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feat = kaldi.fbank(
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x.unsqueeze(0), # append channel dim, (C, Ti)
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n_mels=self.n_mels,
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frame_length=self.n_frame_length,
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frame_shift=self.n_frame_shift,
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dither=self.dither,
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energy_floor=self.energy_floor,
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sr=self.fs)
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assert feat.ndim == 2 # (T,D)
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return feat
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