File size: 3,484 Bytes
70b2a7b 81569b0 70b2a7b 81569b0 70b2a7b 81569b0 70b2a7b 81569b0 70b2a7b 81569b0 70b2a7b 81569b0 70b2a7b 81569b0 2996a98 81569b0 70b2a7b 81569b0 70b2a7b 81569b0 70b2a7b 81569b0 70b2a7b 81569b0 70b2a7b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 |
# ################################
# Model: Transformer ASR
# Augmentation: SpecAugment
# Authors: Pooneh Mousavi 2023
# ################################
# Feature parameters (FBANKS etc)
sample_rate: 16000
n_fft: 400
n_mels: 80
# Model parameters
# Transformer
d_model: 768
nhead: 8
num_encoder_layers: 12
num_decoder_layers: 6
d_ffn: 3072
transformer_dropout: 0.0
activation: !name:torch.nn.GELU
output_neurons: 500
# Outputs
blank_index: 0
label_smoothing: 0.1
pad_index: 0
bos_index: 1
eos_index: 2
# Decoding parameters
min_decode_ratio: 0.0
max_decode_ratio: 1.0
valid_search_interval: 5
valid_beam_size: 10
test_beam_size: 80
ctc_weight_decode: 0.3
scorer_beam_scale: 0.3
transformer_beam_search: True
normalizer: !new:speechbrain.processing.features.InputNormalization
norm_type: global
compute_features: !new:speechbrain.lobes.features.Fbank
sample_rate: !ref <sample_rate>
n_fft: !ref <n_fft>
n_mels: !ref <n_mels>
CNN: !new:speechbrain.lobes.models.convolution.ConvolutionFrontEnd
input_shape: (8, 10, 80)
num_blocks: 3
num_layers_per_block: 1
out_channels: (128, 200, 256)
kernel_sizes: (3, 3, 1)
strides: (2, 2, 1)
residuals: (False, False, False)
Transformer: !new:speechbrain.lobes.models.transformer.TransformerASR.TransformerASR # yamllint disable-line rule:line-length
input_size: 5120
tgt_vocab: !ref <output_neurons>
d_model: !ref <d_model>
nhead: !ref <nhead>
num_encoder_layers: !ref <num_encoder_layers>
num_decoder_layers: !ref <num_decoder_layers>
d_ffn: !ref <d_ffn>
dropout: !ref <transformer_dropout>
activation: !ref <activation>
normalize_before: False
causal: False
ctc_lin: !new:speechbrain.nnet.linear.Linear
input_size: !ref <d_model>
n_neurons: !ref <output_neurons>
seq_lin: !new:speechbrain.nnet.linear.Linear
input_size: !ref <d_model>
n_neurons: !ref <output_neurons>
log_softmax: !new:speechbrain.nnet.activations.Softmax
apply_log: True
# Scorer
ctc_scorer: !new:speechbrain.decoders.scorer.CTCScorer
eos_index: !ref <eos_index>
blank_index: !ref <blank_index>
ctc_fc: !ref <ctc_lin>
scorer: !new:speechbrain.decoders.scorer.ScorerBuilder
full_scorers: [!ref <ctc_scorer>]
weights:
ctc: !ref <ctc_weight_decode>
scorer_beam_scale: !ref <scorer_beam_scale>
asr_model: !new:torch.nn.ModuleList
- [!ref <CNN>, !ref <Transformer>, !ref <seq_lin>, !ref <ctc_lin>]
tokenizer: !new:sentencepiece.SentencePieceProcessor
# We compose the inference (encoder) pipeline.
encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential
input_shape: [null, null, !ref <n_mels>]
compute_features: !ref <compute_features>
normalize: !ref <normalizer>
CNN: !ref <CNN>
decoder: !new:speechbrain.decoders.S2STransformerBeamSearcher
modules: [!ref <Transformer>, !ref <seq_lin>]
bos_index: !ref <bos_index>
eos_index: !ref <eos_index>
min_decode_ratio: !ref <min_decode_ratio>
max_decode_ratio: !ref <max_decode_ratio>
beam_size: !ref <test_beam_size>
temperature: 1.15
using_eos_threshold: True
scorer: !ref <scorer>
modules:
normalizer: !ref <normalizer>
encoder: !ref <encoder>
transformer: !ref <Transformer>
decoder: !ref <decoder>
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
normalizer: !ref <normalizer>
asr: !ref <asr_model>
tokenizer: !ref <tokenizer> |