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embedding_model.ckpt

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+size 83316686

hyperparams.yaml

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+# ############################################################################
+# Model:
+# Author:
+# ############################################################################
+
+# Feature parameters
+sample_rate: 16000
+time_resolution: 0.01 # in seconds (e.g,, 0.01 = 10 ms)
+n_fft: 400
+n_mels_vad: 40
+batch_size: 512
+
+# VAD parameters
+cnn1_channels: 16
+cnn2_channels: 32
+cnn_kernelsize: (3, 3)
+rnn_layers: 2
+rnn_neurons: 32
+rnn_bidirectional: True
+dnn_blocks: 1
+dnn_neurons: 16
+output_neurons_vad: 1
+
+# ECAPA_TDNN
+n_mels_ecapa: 80
+out_neurons_ecapa: 7205
+emb_dim: 192
+
+dataloader_opts:
+  batch_size: !ref <batch_size>
+
+# VAD objects
+compute_fbank_vad: !new:speechbrain.lobes.features.Fbank
+  sample_rate: !ref <sample_rate>
+  n_fft: !ref <n_fft>
+  n_mels: !ref <n_mels_vad>
+  hop_length: !ref <time_resolution> * 1000 # in ms
+
+mean_var_norm_vad: !new:speechbrain.processing.features.InputNormalization
+  norm_type: sentence
+
+cnn: !new:speechbrain.nnet.containers.Sequential
+  input_shape: [null, null, !ref <n_mels_vad>]
+  norm1: !name:speechbrain.nnet.normalization.LayerNorm
+  cnn1: !name:speechbrain.lobes.models.CRDNN.CNN_Block
+    channels: !ref <cnn1_channels>
+    kernel_size: !ref <cnn_kernelsize>
+  cnn2: !name:speechbrain.lobes.models.CRDNN.CNN_Block
+    channels: !ref <cnn2_channels>
+    kernel_size: !ref <cnn_kernelsize>
+
+rnn: !new:speechbrain.nnet.RNN.GRU
+  input_shape: [null, null, 320]
+  hidden_size: !ref <rnn_neurons>
+  num_layers: !ref <rnn_layers>
+  bidirectional: !ref <rnn_bidirectional>
+
+dnn: !new:speechbrain.nnet.containers.Sequential
+  input_shape: [null, null, !ref <rnn_neurons> * 2]
+  dnn1: !name:speechbrain.lobes.models.CRDNN.DNN_Block
+    neurons: !ref <dnn_neurons>
+  dnn2: !name:speechbrain.lobes.models.CRDNN.DNN_Block
+    neurons: !ref <dnn_neurons>
+  lin: !name:speechbrain.nnet.linear.Linear
+    n_neurons: !ref <output_neurons_vad>
+    bias: False
+##########################################################
+
+# ECAPA_TDNN objects
+compute_fbank_ecapa: !new:speechbrain.lobes.features.Fbank
+  n_mels: !ref <n_mels_ecapa>
+
+mean_var_norm_ecapa: !new:speechbrain.processing.features.InputNormalization
+  norm_type: sentence
+  std_norm: False
+
+embedding_model: !new:speechbrain.lobes.models.ECAPA_TDNN.ECAPA_TDNN
+  input_size: !ref <n_mels_ecapa>
+  channels: [1024, 1024, 1024, 1024, 3072]
+  kernel_sizes: [5, 3, 3, 3, 1]
+  dilations: [1, 2, 3, 4, 1]
+  attention_channels: 128
+  lin_neurons: 192
+
+mean_var_norm_emb: !new:speechbrain.processing.features.InputNormalization
+  norm_type: global
+  std_norm: False
+#####################
+
+vad: !new:torch.nn.ModuleList
+  - [!ref <cnn>, !ref <rnn>, !ref <dnn>]
+
+#####################
+modules:
+  compute_fbank_vad: !ref <compute_fbank_vad>
+  compute_fbank_ecapa: !ref <compute_fbank_ecapa>
+  cnn: !ref <cnn>
+  rnn: !ref <rnn>
+  dnn: !ref <dnn>
+  mean_var_norm_vad: !ref <mean_var_norm_vad>
+  mean_var_norm_ecapa: !ref <mean_var_norm_ecapa>
+  embedding_model: !ref <embedding_model>
+  mean_var_norm_emb: !ref <mean_var_norm_emb>
+
+pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
+  loadables:
+    vad: !ref <vad>
+    embedding_model: !ref <embedding_model>
+    mean_var_norm_vad: !ref <mean_var_norm_vad>
+    mean_var_norm_emb: !ref <mean_var_norm_emb>

mean_var_norm_emb.ckpt

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+oid sha256:cd70225b05b37be64fc5a95e24395d804231d43f74b2e1e5a513db7b69b34c33
+size 1921

mean_var_norm_vad.ckpt

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+size 1063

vad.ckpt

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