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sample_rate: 16000
# BPE parameters
token_type: unigram # ["unigram", "bpe", "char"]
character_coverage: 1.0
# Model parameters
activation: !name:torch.nn.GELU
wav2vec_output_dim: 1024
dnn_neurons: 1024
freeze_wav2vec: false
dropout: 0.2
# Outputs
output_neurons: 80 # BPE size, index(blank/eos/bos) = 0
tokenizer: !new:sentencepiece.SentencePieceProcessor
# Decoding parameters
# Be sure that the bos and eos index match with the BPEs ones
blank_index: 0
bos_index: 1
eos_index: 2
enc: &id002 !new:speechbrain.nnet.containers.Sequential
input_shape: [null, null, 1024]
linear1: !name:speechbrain.nnet.linear.Linear
n_neurons: 1024
bias: true
bn1: !name:speechbrain.nnet.normalization.BatchNorm1d
activation: !new:torch.nn.GELU
drop: !new:torch.nn.Dropout
p: 0.2
linear2: !name:speechbrain.nnet.linear.Linear
n_neurons: 1024
bias: true
bn2: !name:speechbrain.nnet.normalization.BatchNorm1d
activation2: !new:torch.nn.GELU
drop2: !new:torch.nn.Dropout
p: 0.2
linear3: !name:speechbrain.nnet.linear.Linear
n_neurons: 1024
bias: true
bn3: !name:speechbrain.nnet.normalization.BatchNorm1d
activation3: !new:torch.nn.GELU
wav2vec2: !new:speechbrain.lobes.models.huggingface_wav2vec.HuggingFaceWav2Vec2
source: asafaya/hubert-large-arabic-transcribe
output_norm: true
freeze: false
save_path: wav2vec2_checkpoint
ctc_lin: !new:speechbrain.nnet.linear.Linear
input_size: 1024
n_neurons: 80
log_softmax: !new:speechbrain.nnet.activations.Softmax
apply_log: true
ctc_cost: !name:speechbrain.nnet.losses.ctc_loss
blank_index: 0
modules:
encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential
wav2vec2: !ref <wav2vec2>
enc: !ref <enc>
ctc_lin: !ref <ctc_lin>
model: !new:torch.nn.ModuleList
- [!ref <enc>, !ref <ctc_lin>]
error_rate_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats
cer_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats
split_tokens: true
decoding_function: !name:speechbrain.decoders.ctc.ctc_greedy_decode
blank_id: !ref <blank_index>
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
wav2vec2: !ref <wav2vec2>
model: !ref <model>
tokenizer: !ref <tokenizer>
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