slu-wav2vec2-ctc-MEDIA-full / hyperparams.yaml
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# ################################
# Model: Wav2Vec + DNN + CTC + Softmax
# Authors:
# Gaelle Laperriere 2023
# ################################
wav2vec_url: LeBenchmark/wav2vec2-FR-3K-large
# Feature parameters:
sample_rate: 16000
feats_dim: 1024
# Model parameters:
activation: !name:torch.nn.LeakyReLU
dnn_blocks: 3
dnn_neurons: 512
log_softmax: !new:torch.nn.LogSoftmax
dim: -1
# Decoding parameters:
blank_index: 0
# Outputs:
output_neurons: 212
# ------ Functions and classes
wav2vec2: !new:speechbrain.lobes.models.huggingface_transformers.wav2vec2.Wav2Vec2
source: !ref <wav2vec_url>
output_norm: True
freeze: True
save_path: wav2vec2_checkpoint
enc: !new:speechbrain.lobes.models.VanillaNN.VanillaNN
input_shape: [null, null, !ref <feats_dim>]
activation: !ref <activation>
dnn_blocks: !ref <dnn_blocks>
dnn_neurons: !ref <dnn_neurons>
output_lin: !new:speechbrain.nnet.linear.Linear
input_size: !ref <dnn_neurons>
n_neurons: !ref <output_neurons>
bias: True
model: !new:torch.nn.ModuleList
- [!ref <enc>, !ref <output_lin>]
tokenizer: !new:speechbrain.dataio.encoder.CTCTextEncoder
encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential
wav2vec2: !ref <wav2vec2>
enc: !ref <enc>
output_lin: !ref <output_lin>
log_softmax: !ref <log_softmax>
decoding_function: !name:speechbrain.decoders.ctc_greedy_decode
blank_id: !ref <blank_index>
modules:
encoder: !ref <encoder>
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
wav2vec2: !ref <wav2vec2>
model: !ref <model>
tokenizer: !ref <tokenizer>