File size: 4,427 Bytes
ca4cef6 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 |
# ############################################################################
# model: Seq2Seq
# encoder: CRDNN model
# decoder: GRU + beamsearch
# tokens: BPE (unigram)
# losses: CTC+NLL
# training: Mozilla Common Voice 6.1, Spoken Wikipedia Corpus, M-AILABS Corpus
# authors: Ruhr-University Bochum 2021
# adapted from
# Ju-Chieh Chou,
# Mirco Ravanelli,
# Abdel Heba,
# Peter Plantinga,
# Samuele Cornell,
# Sung-Lin Yeh,
# Titouan Parcollet 2021
# ############################################################################
# set exp name
name: german-asr
# Feature parameters
sample_rate: 16000
n_fft: 400
n_mels: 40
# Model parameters
activation: !name:torch.nn.LeakyReLU
dropout: 0.15
cnn_blocks: 2
cnn_channels: (64, 128)
inter_layer_pooling_size: (2, 2)
cnn_kernelsize: (3, 3)
time_pooling_size: 4
rnn_class: !name:speechbrain.nnet.RNN.LSTM
rnn_layers: 4
rnn_neurons: 1024
rnn_bidirectional: True
dnn_blocks: 1
dnn_neurons: 1024
emb_size: 1024
dec_neurons: 1024
output_neurons: 5000 # Number of tokens (same as LM and tokenizer)
# Decoding parameters
blank_index: 0
pad_index: -1
bos_index: 1
eos_index: 2
unk_index: 0
min_decode_ratio: 0.0
max_decode_ratio: 1.0
beam_size: 30
eos_threshold: 1.5
using_max_attn_shift: True
max_attn_shift: 300
ctc_weight_decode: 0.3
ctc_window_size: 300
coverage_penalty: 1.5
temperature: 1.0
# Feature Extraction
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>
# Tokenizer
tokenizer: !new:sentencepiece.SentencePieceProcessor
# Encoder
enc: !new:speechbrain.lobes.models.CRDNN.CRDNN
input_shape: [null, null, !ref <n_mels>]
activation: !ref <activation>
dropout: !ref <dropout>
cnn_blocks: !ref <cnn_blocks>
cnn_channels: !ref <cnn_channels>
cnn_kernelsize: !ref <cnn_kernelsize>
inter_layer_pooling_size: !ref <inter_layer_pooling_size>
time_pooling: True
using_2d_pooling: False
time_pooling_size: !ref <time_pooling_size>
rnn_class: !ref <rnn_class>
rnn_layers: !ref <rnn_layers>
rnn_neurons: !ref <rnn_neurons>
rnn_bidirectional: !ref <rnn_bidirectional>
rnn_re_init: True
dnn_blocks: !ref <dnn_blocks>
dnn_neurons: !ref <dnn_neurons>
use_rnnp: True
# Decoder
emb: !new:speechbrain.nnet.embedding.Embedding
num_embeddings: !ref <output_neurons>
embedding_dim: !ref <emb_size>
dec: !new:speechbrain.nnet.RNN.AttentionalRNNDecoder
enc_dim: !ref <dnn_neurons>
input_size: !ref <emb_size>
rnn_type: gru
attn_type: location
hidden_size: !ref <dec_neurons>
attn_dim: 1024
num_layers: 1
scaling: 1.0
channels: 10
kernel_size: 100
re_init: True
dropout: !ref <dropout>
# Losses
log_softmax: !new:speechbrain.nnet.activations.Softmax
apply_log: True
ctc_lin: !new:speechbrain.nnet.linear.Linear
input_size: !ref <dnn_neurons>
n_neurons: !ref <output_neurons>
seq_lin: !new:speechbrain.nnet.linear.Linear
input_size: !ref <dec_neurons>
n_neurons: !ref <output_neurons>
# Compile model
asr_model: !new:torch.nn.ModuleList
- [!ref <enc>, !ref <emb>, !ref <dec>, !ref <ctc_lin>, !ref <seq_lin>]
# 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>
model: !ref <enc>
# Beam searcher
decoder: !new:speechbrain.decoders.S2SRNNBeamSearcher
embedding: !ref <emb>
decoder: !ref <dec>
linear: !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 <beam_size>
eos_threshold: !ref <eos_threshold>
using_max_attn_shift: !ref <using_max_attn_shift>
max_attn_shift: !ref <max_attn_shift>
temperature: !ref <temperature>
modules:
normalizer: !ref <normalizer>
encoder: !ref <encoder>
decoder: !ref <decoder>
# Load pretrained models
pretrainer: !new:speechbrain.utils.parameter_transfer.Pretrainer
loadables:
asr: !ref <asr_model>
tokenizer: !ref <tokenizer>
normalizer: !ref <normalizer>
|