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# ################################
# Model: wav2vec2 + DNN + CTC
# Augmentation: SpecAugment
# Authors: Sung-Lin Yeh 2021, Titouan Parcollet 2022
# ################################
# URL for the biggest Fairseq english wav2vec2 model.
wav2vec2_hub: facebook/wav2vec2-large-960h-lv60-self
sample_rate: 16000
# Model parameters
activation: !name:torch.nn.LeakyReLU
dnn_layers: 2
dnn_neurons: 1024
freeze_wav2vec: True
# Outputs
output_neurons: 31 # BPE size, index(blank/eos/bos) = 0
# Decoding parameters
blank_index: 0
bos_index: 1
eos_index: 2
enc: !new:speechbrain.lobes.models.VanillaNN.VanillaNN
input_shape: [null, null, 1024]
activation: !ref <activation>
dnn_blocks: !ref <dnn_layers>
dnn_neurons: !ref <dnn_neurons>
wav2vec2: !new:speechbrain.lobes.models.huggingface_transformers.Wav2Vec2
source: !ref <wav2vec2_hub>
output_norm: True
freeze: True
save_path: model_checkpoints
ctc_lin: !new:speechbrain.nnet.linear.Linear
input_size: !ref <dnn_neurons>
n_neurons: !ref <output_neurons>
log_softmax: !new:speechbrain.nnet.activations.Softmax
apply_log: True
ctc_cost: !name:speechbrain.nnet.losses.ctc_loss
blank_index: !ref <blank_index>
asr_model: !new:torch.nn.ModuleList
- [!ref <enc>, !ref <ctc_lin>]
tokenizer: !new:speechbrain.dataio.encoder.CTCTextEncoder
encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential
wav2vec2: !ref <wav2vec2>
enc: !ref <enc>
ctc_lin: !ref <ctc_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>
asr: !ref <asr_model>
tokenizer: !ref <tokenizer> |