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# ############################################################################
# Model: WavLM for Emotion Diarization
# ############################################################################
# Hparams NEEDED
HPARAMS_NEEDED: ["window_length", "stride", "encoder_dim", "out_n_neurons", "avg_pool", "label_encoder", "softmax"]
# Modules Needed
MODULES_NEEDED: ["wav2vec2", "output_mlp"]
# Feature parameters
wav2vec2_hub: "microsoft/wavlm-large"
# Pretrain folder (HuggingFace)
pretrained_path: /home/ywang/zed_pr/sed_hf
# parameters
window_length: 1 # win_len = 0.02 * 1 = 0.02s
stride: 1 # stride = 0.02 * 1 = 0.02s
encoder_dim: 1024
out_n_neurons: 4
input_norm: !new:speechbrain.processing.features.InputNormalization
norm_type: sentence
std_norm: False
wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2
source: !ref <wav2vec2_hub>
output_norm: True
freeze: False
freeze_feature_extractor: True
save_path: wav2vec2_checkpoint
avg_pool: !new:speechbrain.nnet.pooling.Pooling1d
pool_type: "avg"
kernel_size: !ref <window_length>
stride: !ref <stride>
ceil_mode: True
output_mlp: !new:speechbrain.nnet.linear.Linear
input_size: !ref <encoder_dim>
n_neurons: !ref <out_n_neurons>
bias: False
model: !new:torch.nn.ModuleList
- [!ref <output_mlp>]
modules:
input_norm: !ref <input_norm>
wav2vec2: !ref <wav2vec2>
output_mlp: !ref <output_mlp>
log_softmax: !new:speechbrain.nnet.activations.Softmax
apply_log: True
label_encoder: !new:speechbrain.dataio.encoder.CategoricalEncoder
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
input_norm: !ref <input_norm>
wav2vec2: !ref <wav2vec2>
model: !ref <model>
label_encoder: !ref <label_encoder>
paths:
input_norm: !ref <pretrained_path>/input_norm.ckpt
wav2vec2: !ref <pretrained_path>/wav2vec2.ckpt
model: !ref <pretrained_path>/model.ckpt
label_encoder: !ref <pretrained_path>/label_encoder.txt
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