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Use much more aggressive SpecAug setup

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This commit is contained in:
Daniel Povey 2022-02-08 21:55:20 +08:00
parent beaf5bfbab
commit bd36216e8c
1 changed files with 3 additions and 3 deletions
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6
egs/librispeech/ASR/tdnn_lstm_ctc/asr_datamodule.py
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@ -220,7 +220,7 @@ class LibriSpeechAsrDataModule:
time_warp_factor=self.args.spec_aug_time_warp_factor,
num_frame_masks=10,
features_mask_size=27,
num_feature_masks=2,
num_feature_masks=10,
frames_mask_size=100,
max_frames_mask_fraction=0.4,
)
@ -521,7 +521,7 @@ class SpecAugment(torch.nn.Module):
_max_tot_mask_frames = self.max_frames_mask_fraction * features.size(0)
num_frame_masks = min(self.num_frame_masks, math.ceil(_max_tot_mask_frames / self.frames_mask_size))
max_mask_frames = min(self.frames_mask_size, _max_tot_mask_frames // num_frame_masks)
features = mask_along_axis(
features.unsqueeze(0),
mask_param=max_mask_frames,
@ -591,4 +591,4 @@ def time_warp(features: torch.Tensor, factor: int) -> torch.Tensor:
mode="bicubic",
align_corners=False,
)
return torch.cat((left, right), dim=2).squeeze(0).squeeze(0)
return torch.cat((left, right), dim=2).squeeze(0).squeeze(0)