Hugging Face's logo

SalahZa
/
Code_Switched_Tunisian_Speech_Recognition

Model card Files Community
Code_Switched_Tunisian_Speech_Recognition
File size: 3,989 Bytes 
0d1350d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ed25c49
0d1350d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
 
# Generated 2023-08-03 from:
# /home/salah/new_tunisian_model/hparams/train_tunisian_withwavlm.yaml
# yamllint disable
# ################################
# Model: wav2vec2 + DNN + CTC
# Augmentation: SpecAugment
# Authors: Titouan Parcollet 2021
# ################################

seed: 1994
__set_seed: !!python/object/apply:torch.manual_seed [1234]
output_folder: results/non_semi_final_stac
wer_file: !ref <output_folder>/wer.txt
save_folder: !ref <output_folder>/save
train_log: !ref <output_folder>/train_log.txt



# Data files
data_folder: junk  # e.g, /localscratch/cv-corpus-5.1-2020-06-22/fr
train_tsv_file: junk/train.tsv                # Standard CommonVoice .tsv files
dev_tsv_file: junk/dev.tsv                # Standard CommonVoice .tsv files
test_tsv_file: junk/test.tsv                # Standard CommonVoice .tsv files
accented_letters: true

csv_folder: /gpfsscratch/rech/nou/uzn19yk/switched_data/extended_clean/
train_csv: !ref <csv_folder>/train.csv
valid_csv: !ref <csv_folder>/dev.csv
test_csv:
        - all_tests/cs_test.csv
        - all_tests/stac_test.csv

# We remove utterance slonger than 10s in the train/dev/test sets as
# longer sentences certainly correspond to "open microphones".
avoid_if_longer_than: 13.0
avoid_if_shorter_than: 0.5

# Training parameters
number_of_epochs: 20
lr: 0.0002
lr_weights: 0.01
sorting: ascending
auto_mix_prec: False
sample_rate: 16000
language_modelling: True
ngram_lm_path: arpas/pluslanguages_everything.arpa 

# With data_parallel batch_size is split into N jobs
# With DDP batch_size is multiplied by N jobs
# Must be 3 per GPU to fit 32GB of VRAM
batch_size: 3
test_batch_size: 4

# Dataloader options
dataloader_options:
    batch_size: !ref <batch_size>
    num_workers: 6

test_dataloader_options:
    batch_size: !ref <test_batch_size>
    num_workers: 6

# Model parameters
activation: !name:torch.nn.Sigmoid
dnn_layers: 1
dnn_neurons: 768
freeze_encoder: True

# Outputs
output_neurons: 76  # BPE size, index(blank/eos/bos) = 0

# Functions and classes
#
epoch_counter: !new:speechbrain.utils.epoch_loop.EpochCounter
   limit: !ref <number_of_epochs>

encoder_dim: 3217 
enc: !new:speechbrain.nnet.RNN.LSTM
   input_shape: [Null, Null, !ref <encoder_dim>]
   num_layers: 2
   bidirectional: True
   dropout: 0.2
   hidden_size: 1024

ctc_lin: !new:speechbrain.nnet.linear.Linear
   input_size: 2048
   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>

modules:
   enc: !ref <enc>
   ctc_lin: !ref <ctc_lin>

model: !new:torch.nn.ModuleList
   - [!ref <enc>, !ref <ctc_lin>]

model_opt_class: !name:torch.optim.Adam
   lr: !ref <lr>

weights_opt_class: !name:torch.optim.Adam
   lr: !ref <lr_weights>

lr_annealing_model: !new:speechbrain.nnet.schedulers.NewBobScheduler
   initial_value: !ref <lr>
   improvement_threshold: 0.0025
   annealing_factor: 0.8
   patient: 0

lr_annealing_weights: !new:speechbrain.nnet.schedulers.NewBobScheduler
   initial_value: !ref <lr_weights>
   improvement_threshold: 0.0025
   annealing_factor: 0.9
   patient: 0

label_encoder: !new:speechbrain.dataio.encoder.CTCTextEncoder

checkpointer: !new:speechbrain.utils.checkpoints.Checkpointer
   checkpoints_dir: !ref <save_folder>
   recoverables:
      model: !ref <model>
      scheduler_model: !ref <lr_annealing_model>
      scheduler_encoder: !ref <lr_annealing_weights>
      counter: !ref <epoch_counter>
      tokenizer: !ref <label_encoder>

blank_index: 0
unk_index: 1


train_logger: !new:speechbrain.utils.train_logger.FileTrainLogger
   save_file: !ref <train_log>

error_rate_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats

cer_computer: !name:speechbrain.utils.metric_stats.ErrorRateStats
   split_tokens: True