diff --git a/egs/librispeech/ASR/conformer_ctc/subsampling.py b/egs/librispeech/ASR/conformer_ctc/subsampling.py index a66421adf..e38a94d09 100644 --- a/egs/librispeech/ASR/conformer_ctc/subsampling.py +++ b/egs/librispeech/ASR/conformer_ctc/subsampling.py @@ -48,12 +48,12 @@ class Conv2dSubsampling(nn.Module): in_channels=1, out_channels=odim, kernel_size=3, stride=2 ), nn.ReLU(), - ExpScale(odim, 1, 1, speed=4.0), + ExpScale(odim, 1, 1, speed=20.0), nn.Conv2d( in_channels=odim, out_channels=odim, kernel_size=3, stride=2 ), nn.ReLU(), - ExpScale(odim, 1, 1, speed=4.0), + ExpScale(odim, 1, 1, speed=20.0), ) self.out = nn.Linear(odim * (((idim - 1) // 2 - 1) // 2), odim) self.out_norm = nn.LayerNorm(odim, elementwise_affine=False) diff --git a/egs/librispeech/ASR/transducer_stateless/conformer.py b/egs/librispeech/ASR/transducer_stateless/conformer.py index 83e0f8bca..6907feb26 100644 --- a/egs/librispeech/ASR/transducer_stateless/conformer.py +++ b/egs/librispeech/ASR/transducer_stateless/conformer.py @@ -156,7 +156,7 @@ class ConformerEncoderLayer(nn.Module): self.feed_forward = nn.Sequential( nn.Linear(d_model, dim_feedforward), - ExpScaleSwish(dim_feedforward, speed=4.0), + ExpScaleSwish(dim_feedforward, speed=20.0), nn.Dropout(dropout), nn.Linear(dim_feedforward, d_model), ) @@ -164,7 +164,7 @@ class ConformerEncoderLayer(nn.Module): self.feed_forward_macaron = nn.Sequential( nn.Linear(d_model, dim_feedforward), Swish(), - ExpScaleSwish(dim_feedforward, speed=4.0), + ExpScaleSwish(dim_feedforward, speed=20.0), nn.Dropout(dropout), nn.Linear(dim_feedforward, d_model), ) diff --git a/egs/librispeech/ASR/transducer_stateless/train.py b/egs/librispeech/ASR/transducer_stateless/train.py index a1ded87c6..c57968428 100755 --- a/egs/librispeech/ASR/transducer_stateless/train.py +++ b/egs/librispeech/ASR/transducer_stateless/train.py @@ -110,7 +110,7 @@ def get_parser(): parser.add_argument( "--exp-dir", type=str, - default="transducer_stateless/specaugmod_baseline_randcombine1_expscale2", + default="transducer_stateless/specaugmod_baseline_randcombine1_expscale3", help="""The experiment dir. It specifies the directory where all training related files, e.g., checkpoints, log, etc, are saved