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PaddleSpeech/examples/aishell/s0/conf/deepspeech2_online.yaml

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# https://yaml.org/type/float.html
data:
train_manifest: data/manifest.train
dev_manifest: data/manifest.dev
test_manifest: data/manifest.test
min_input_len: 0.0
max_input_len: 27.0 # second
min_output_len: 0.0
max_output_len: .inf
min_output_input_ratio: 0.00
max_output_input_ratio: .inf
collator:
batch_size: 64 # one gpu
mean_std_filepath: data/mean_std.json
unit_type: char
vocab_filepath: data/vocab.txt
augmentation_config: conf/augmentation.json
random_seed: 0
spm_model_prefix:
specgram_type: linear #linear, mfcc, fbank
feat_dim:
delta_delta: False
stride_ms: 10.0
window_ms: 20.0
n_fft: None
max_freq: None
target_sample_rate: 16000
use_dB_normalization: True
target_dB: -20
dither: 1.0
keep_transcription_text: False
sortagrad: True
shuffle_method: batch_shuffle
num_workers: 0
model:
num_conv_layers: 2
num_rnn_layers: 5
rnn_layer_size: 1024
rnn_direction: forward # [forward, bidirect]
num_fc_layers: 0
fc_layers_size_list: -1,
use_gru: False
blank_id: 0
ctc_grad_norm_type: instance
training:
n_epoch: 50
accum_grad: 1
lr: 2e-3
lr_decay: 0.9 # 0.83
weight_decay: 1e-06
global_grad_clip: 3.0
log_interval: 100
checkpoint:
kbest_n: 50
latest_n: 5
decoding:
batch_size: 32
error_rate_type: cer
decoding_method: ctc_beam_search
lang_model_path: data/lm/zh_giga.no_cna_cmn.prune01244.klm
alpha: 2.2 #1.9
beta: 5.0
beam_size: 300
cutoff_prob: 0.99
cutoff_top_n: 40
num_proc_bsearch: 10