add test wavs

README.md

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+Note: This recipe is trained with the codes from this PR https://github.com/k2-fsa/icefall/pull/378
+And the SpecAugment codes from this PR https://github.com/lhotse-speech/lhotse/pull/604.
+# Pre-trained Transducer-Stateless2 models for the Alimeeting dataset with icefall.
+The model was trained on the far data of [Alimeeting](https://www.openslr.org/119) with the scripts in [icefall](https://github.com/k2-fsa/icefall) based on the latest version k2.  
+## Training procedure
+The main repositories are list below, we will update the training and decoding scripts with the update of version.  
+k2: https://github.com/k2-fsa/k2 
+icefall: https://github.com/k2-fsa/icefall 
+lhotse: https://github.com/lhotse-speech/lhotse
+* Install k2 and lhotse, k2 installation guide refers to https://k2.readthedocs.io/en/latest/installation/index.html, lhotse refers to https://lhotse.readthedocs.io/en/latest/getting-started.html#installation. I think the latest version would be ok. And please also install the requirements listed in icefall.
+* Clone icefall(https://github.com/k2-fsa/icefall) and check to the commit showed above.
+```
+git clone https://github.com/k2-fsa/icefall
+cd icefall
+```
+* Preparing data.
+```
+cd egs/alimeeting/ASR
+bash ./prepare.sh
+```
+* Training
+```
+export CUDA_VISIBLE_DEVICES="0,1,2,3"
+./pruned_transducer_stateless2/train.py \
+                  --world-size 4 \
+                  --num-epochs 30 \
+                  --start-epoch 0 \
+                  --exp-dir pruned_transducer_stateless2/exp \
+                  --lang-dir data/lang_char \
+                  --max-duration 220
+```
+## Evaluation results
+The decoding results (WER%) on Alimeeting(eval and test) are listed below, we got this result by averaging models from epoch 12 to 29.
+The WERs are
+|                                    |     eval   |    test    | comment                                  |
+|------------------------------------|------------|------------|------------------------------------------|
+|          greedy search             | 31.77      | 34.66      | --epoch 29, --avg 18, --max-duration 100 |
+| modified beam search (beam size 4) | 30.38      | 33.02      | --epoch 29, --avg 18, --max-duration 100 |
+| fast beam search (set as default)  | 31.39      | 34.25      | --epoch 29, --avg 18, --max-duration 1500|
+

data/lang_char/Linv.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:01f6abfcb9f36a0dd22e8a41c2cce304af2292a8f530d69e48108bcde2b7edcd
+size 1750119

data/lang_char/tokens.txt

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exp/pretrained_epoch_29_avg_18.pt

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log/fast_beam_search/log-decode-epoch-29-avg-18-beam-4-max-contexts-4-max-states-8-2022-05-31-17-45-54

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+2022-05-31 17:45:54,602 INFO [decode.py:472] Decoding started
+2022-05-31 17:45:54,602 INFO [decode.py:478] Device: cuda:0
+2022-05-31 17:45:54,693 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
+2022-05-31 17:45:54,706 INFO [decode.py:484] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 10, 'log_interval': 1, 'reset_interval': 200, 'valid_interval': 400, 'feature_dim': 80, 'subsampling_factor': 4, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'decoder_dim': 512, 'joiner_dim': 512, 'model_warm_step': 200, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.2.0.dev+git.de75634.dirty', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt2-ali-meeting', 'icefall-git-sha1': '5e507f3-dirty', 'icefall-git-date': 'Fri May 20 01:47:19 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.2.0.dev0+git.de75634.dirty-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-6-0415002726-7dc5bf9fdc-w24k9', 'IP address': '10.177.28.71'}, 'epoch': 29, 'batch': None, 'avg': 18, 'avg_last_n': 0, 'exp_dir': PosixPath('pruned_transducer_stateless2/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'fast_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 1500, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless2/exp/fast_beam_search'), 'suffix': 'epoch-29-avg-18-beam-4-max-contexts-4-max-states-8', 'blank_id': 0, 'vocab_size': 3318}
+2022-05-31 17:45:54,706 INFO [decode.py:486] About to create model
+2022-05-31 17:45:55,363 INFO [decode.py:507] averaging ['pruned_transducer_stateless2/exp/epoch-12.pt', 'pruned_transducer_stateless2/exp/epoch-13.pt', 'pruned_transducer_stateless2/exp/epoch-14.pt', 'pruned_transducer_stateless2/exp/epoch-15.pt', 'pruned_transducer_stateless2/exp/epoch-16.pt', 'pruned_transducer_stateless2/exp/epoch-17.pt', 'pruned_transducer_stateless2/exp/epoch-18.pt', 'pruned_transducer_stateless2/exp/epoch-19.pt', 'pruned_transducer_stateless2/exp/epoch-20.pt', 'pruned_transducer_stateless2/exp/epoch-21.pt', 'pruned_transducer_stateless2/exp/epoch-22.pt', 'pruned_transducer_stateless2/exp/epoch-23.pt', 'pruned_transducer_stateless2/exp/epoch-24.pt', 'pruned_transducer_stateless2/exp/epoch-25.pt', 'pruned_transducer_stateless2/exp/epoch-26.pt', 'pruned_transducer_stateless2/exp/epoch-27.pt', 'pruned_transducer_stateless2/exp/epoch-28.pt', 'pruned_transducer_stateless2/exp/epoch-29.pt']
+2022-05-31 17:46:19,875 INFO [decode.py:521] Number of model parameters: 84427758
+2022-05-31 17:46:19,877 INFO [asr_datamodule.py:339] About to create dev dataset
+2022-05-31 17:46:22,343 INFO [asr_datamodule.py:358] About to create dev dataloader
+2022-05-31 17:46:32,914 INFO [decode.py:392] batch 0/?, cuts processed until now is 89
+2022-05-31 17:47:08,801 INFO [decode.py:409] The transcripts are stored in pruned_transducer_stateless2/exp/fast_beam_search/recogs-dev-beam_4_max_contexts_4_max_states_8-epoch-29-avg-18-beam-4-max-contexts-4-max-states-8.txt
+2022-05-31 17:47:08,972 INFO [utils.py:406] [dev-beam_4_max_contexts_4_max_states_8] %WER 31.39% [27249 / 86810, 2112 ins, 11290 del, 13847 sub ]
+2022-05-31 17:47:09,495 INFO [decode.py:422] Wrote detailed error stats to pruned_transducer_stateless2/exp/fast_beam_search/errs-dev-beam_4_max_contexts_4_max_states_8-epoch-29-avg-18-beam-4-max-contexts-4-max-states-8.txt
+2022-05-31 17:47:09,497 INFO [decode.py:439] 
+For dev, WER of different settings are:
+beam_4_max_contexts_4_max_states_8	31.39	best for dev
+
+2022-05-31 17:47:18,088 INFO [decode.py:392] batch 0/?, cuts processed until now is 202
+2022-05-31 17:48:43,374 INFO [decode.py:409] The transcripts are stored in pruned_transducer_stateless2/exp/fast_beam_search/recogs-test-beam_4_max_contexts_4_max_states_8-epoch-29-avg-18-beam-4-max-contexts-4-max-states-8.txt
+2022-05-31 17:48:43,828 INFO [utils.py:406] [test-beam_4_max_contexts_4_max_states_8] %WER 34.25% [77469 / 226178, 5142 ins, 34902 del, 37425 sub ]
+2022-05-31 17:48:45,226 INFO [decode.py:422] Wrote detailed error stats to pruned_transducer_stateless2/exp/fast_beam_search/errs-test-beam_4_max_contexts_4_max_states_8-epoch-29-avg-18-beam-4-max-contexts-4-max-states-8.txt
+2022-05-31 17:48:45,227 INFO [decode.py:439] 
+For test, WER of different settings are:
+beam_4_max_contexts_4_max_states_8	34.25	best for test
+
+2022-05-31 17:48:45,227 INFO [decode.py:602] Done!

log/fast_beam_search/wer-summary-dev-beam_4_max_contexts_4_max_states_8-epoch-29-avg-18-beam-4-max-contexts-4-max-states-8.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_4_max_contexts_4_max_states_8	31.39

log/fast_beam_search/wer-summary-test-beam_4_max_contexts_4_max_states_8-epoch-29-avg-18-beam-4-max-contexts-4-max-states-8.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_4_max_contexts_4_max_states_8	34.25

log/greedy_search/log-decode-epoch-29-avg-18-context-2-max-sym-per-frame-1-2022-05-31-20-19-42

@@ -0,0 +1,6 @@
+2022-05-31 20:19:42,698 INFO [decode.py:472] Decoding started
+2022-05-31 20:19:42,698 INFO [decode.py:478] Device: cuda:0
+2022-05-31 20:19:42,789 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
+2022-05-31 20:19:42,802 INFO [decode.py:484] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 10, 'log_interval': 1, 'reset_interval': 200, 'valid_interval': 400, 'feature_dim': 80, 'subsampling_factor': 4, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'decoder_dim': 512, 'joiner_dim': 512, 'model_warm_step': 200, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.2.0.dev+git.de75634.dirty', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt2-ali-meeting', 'icefall-git-sha1': '5e507f3-dirty', 'icefall-git-date': 'Fri May 20 01:47:19 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.2.0.dev0+git.de75634.dirty-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-6-0415002726-7dc5bf9fdc-w24k9', 'IP address': '10.177.28.71'}, 'epoch': 29, 'batch': None, 'avg': 18, 'avg_last_n': 0, 'exp_dir': PosixPath('pruned_transducer_stateless2/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'greedy_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 200.0, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless2/exp/greedy_search'), 'suffix': 'epoch-29-avg-18-context-2-max-sym-per-frame-1', 'blank_id': 0, 'vocab_size': 3318}
+2022-05-31 20:19:42,802 INFO [decode.py:486] About to create model
+2022-05-31 20:19:43,455 INFO [decode.py:507] averaging ['pruned_transducer_stateless2/exp/epoch-12.pt', 'pruned_transducer_stateless2/exp/epoch-13.pt', 'pruned_transducer_stateless2/exp/epoch-14.pt', 'pruned_transducer_stateless2/exp/epoch-15.pt', 'pruned_transducer_stateless2/exp/epoch-16.pt', 'pruned_transducer_stateless2/exp/epoch-17.pt', 'pruned_transducer_stateless2/exp/epoch-18.pt', 'pruned_transducer_stateless2/exp/epoch-19.pt', 'pruned_transducer_stateless2/exp/epoch-20.pt', 'pruned_transducer_stateless2/exp/epoch-21.pt', 'pruned_transducer_stateless2/exp/epoch-22.pt', 'pruned_transducer_stateless2/exp/epoch-23.pt', 'pruned_transducer_stateless2/exp/epoch-24.pt', 'pruned_transducer_stateless2/exp/epoch-25.pt', 'pruned_transducer_stateless2/exp/epoch-26.pt', 'pruned_transducer_stateless2/exp/epoch-27.pt', 'pruned_transducer_stateless2/exp/epoch-28.pt', 'pruned_transducer_stateless2/exp/epoch-29.pt']

log/greedy_search/log-decode-epoch-29-avg-18-context-2-max-sym-per-frame-1-2022-05-31-20-21-08

@@ -0,0 +1,28 @@
+2022-05-31 20:21:08,858 INFO [decode.py:472] Decoding started
+2022-05-31 20:21:08,858 INFO [decode.py:478] Device: cuda:0
+2022-05-31 20:21:08,948 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
+2022-05-31 20:21:08,961 INFO [decode.py:484] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 10, 'log_interval': 1, 'reset_interval': 200, 'valid_interval': 400, 'feature_dim': 80, 'subsampling_factor': 4, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'decoder_dim': 512, 'joiner_dim': 512, 'model_warm_step': 200, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.2.0.dev+git.de75634.dirty', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt2-ali-meeting', 'icefall-git-sha1': '5e507f3-dirty', 'icefall-git-date': 'Fri May 20 01:47:19 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.2.0.dev0+git.de75634.dirty-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-6-0415002726-7dc5bf9fdc-w24k9', 'IP address': '10.177.28.71'}, 'epoch': 29, 'batch': None, 'avg': 18, 'avg_last_n': 0, 'exp_dir': PosixPath('pruned_transducer_stateless2/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'greedy_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 200.0, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless2/exp/greedy_search'), 'suffix': 'epoch-29-avg-18-context-2-max-sym-per-frame-1', 'blank_id': 0, 'vocab_size': 3318}
+2022-05-31 20:21:08,961 INFO [decode.py:486] About to create model
+2022-05-31 20:21:09,620 INFO [decode.py:507] averaging ['pruned_transducer_stateless2/exp/epoch-12.pt', 'pruned_transducer_stateless2/exp/epoch-13.pt', 'pruned_transducer_stateless2/exp/epoch-14.pt', 'pruned_transducer_stateless2/exp/epoch-15.pt', 'pruned_transducer_stateless2/exp/epoch-16.pt', 'pruned_transducer_stateless2/exp/epoch-17.pt', 'pruned_transducer_stateless2/exp/epoch-18.pt', 'pruned_transducer_stateless2/exp/epoch-19.pt', 'pruned_transducer_stateless2/exp/epoch-20.pt', 'pruned_transducer_stateless2/exp/epoch-21.pt', 'pruned_transducer_stateless2/exp/epoch-22.pt', 'pruned_transducer_stateless2/exp/epoch-23.pt', 'pruned_transducer_stateless2/exp/epoch-24.pt', 'pruned_transducer_stateless2/exp/epoch-25.pt', 'pruned_transducer_stateless2/exp/epoch-26.pt', 'pruned_transducer_stateless2/exp/epoch-27.pt', 'pruned_transducer_stateless2/exp/epoch-28.pt', 'pruned_transducer_stateless2/exp/epoch-29.pt']
+2022-05-31 20:21:54,898 INFO [decode.py:525] Number of model parameters: 84427758
+2022-05-31 20:21:54,902 INFO [asr_datamodule.py:339] About to create dev dataset
+2022-05-31 20:21:57,318 INFO [asr_datamodule.py:358] About to create dev dataloader
+2022-05-31 20:22:05,540 INFO [decode.py:392] batch 0/?, cuts processed until now is 25
+2022-05-31 20:22:40,082 INFO [decode.py:409] The transcripts are stored in pruned_transducer_stateless2/exp/greedy_search/recogs-dev-greedy_search-epoch-29-avg-18-context-2-max-sym-per-frame-1.txt
+2022-05-31 20:22:40,257 INFO [utils.py:406] [dev-greedy_search] %WER 31.77% [27581 / 86810, 1921 ins, 11377 del, 14283 sub ]
+2022-05-31 20:22:40,839 INFO [decode.py:422] Wrote detailed error stats to pruned_transducer_stateless2/exp/greedy_search/errs-dev-greedy_search-epoch-29-avg-18-context-2-max-sym-per-frame-1.txt
+2022-05-31 20:22:40,840 INFO [decode.py:439] 
+For dev, WER of different settings are:
+greedy_search	31.77	best for dev
+
+2022-05-31 20:22:46,061 INFO [decode.py:392] batch 0/?, cuts processed until now is 27
+2022-05-31 20:23:26,081 INFO [decode.py:392] batch 100/?, cuts processed until now is 4668
+2022-05-31 20:24:01,906 INFO [decode.py:392] batch 200/?, cuts processed until now is 10119
+2022-05-31 20:24:08,316 INFO [decode.py:409] The transcripts are stored in pruned_transducer_stateless2/exp/greedy_search/recogs-test-greedy_search-epoch-29-avg-18-context-2-max-sym-per-frame-1.txt
+2022-05-31 20:24:08,787 INFO [utils.py:406] [test-greedy_search] %WER 34.66% [78390 / 226178, 4772 ins, 34570 del, 39048 sub ]
+2022-05-31 20:24:10,146 INFO [decode.py:422] Wrote detailed error stats to pruned_transducer_stateless2/exp/greedy_search/errs-test-greedy_search-epoch-29-avg-18-context-2-max-sym-per-frame-1.txt
+2022-05-31 20:24:10,148 INFO [decode.py:439] 
+For test, WER of different settings are:
+greedy_search	34.66	best for test
+
+2022-05-31 20:24:10,148 INFO [decode.py:606] Done!

log/greedy_search/wer-summary-dev-greedy_search-epoch-29-avg-18-context-2-max-sym-per-frame-1.txt

@@ -0,0 +1,2 @@
+settings	WER
+greedy_search	31.77

log/greedy_search/wer-summary-test-greedy_search-epoch-29-avg-18-context-2-max-sym-per-frame-1.txt

@@ -0,0 +1,2 @@
+settings	WER
+greedy_search	34.66

log/modified_beam_search/log-decode-epoch-29-avg-18-beam-4-2022-05-31-17-23-10

@@ -0,0 +1,31 @@
+2022-05-31 17:23:10,279 INFO [decode.py:472] Decoding started
+2022-05-31 17:23:10,279 INFO [decode.py:478] Device: cuda:0
+2022-05-31 17:23:10,402 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
+2022-05-31 17:23:10,415 INFO [decode.py:484] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 10, 'log_interval': 1, 'reset_interval': 200, 'valid_interval': 400, 'feature_dim': 80, 'subsampling_factor': 4, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'decoder_dim': 512, 'joiner_dim': 512, 'model_warm_step': 200, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.2.0.dev+git.de75634.dirty', 'torch-version': '1.11.0', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt2-ali-meeting', 'icefall-git-sha1': '5e507f3-dirty', 'icefall-git-date': 'Fri May 20 01:47:19 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.2.0.dev0+git.de75634.dirty-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-6-0415002726-7dc5bf9fdc-w24k9', 'IP address': '10.177.28.71'}, 'epoch': 29, 'batch': None, 'avg': 18, 'avg_last_n': 0, 'exp_dir': PosixPath('pruned_transducer_stateless2/exp'), 'lang_dir': 'data/lang_char', 'decoding_method': 'modified_beam_search', 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'manifest_dir': PosixPath('data/fbank'), 'max_duration': 200.0, 'bucketing_sampler': True, 'num_buckets': 300, 'concatenate_cuts': False, 'duration_factor': 1.0, 'gap': 1.0, 'on_the_fly_feats': False, 'shuffle': True, 'return_cuts': True, 'num_workers': 2, 'enable_spec_aug': True, 'spec_aug_time_warp_factor': 80, 'enable_musan': True, 'res_dir': PosixPath('pruned_transducer_stateless2/exp/modified_beam_search'), 'suffix': 'epoch-29-avg-18-beam-4', 'blank_id': 0, 'vocab_size': 3318}
+2022-05-31 17:23:10,415 INFO [decode.py:486] About to create model
+2022-05-31 17:23:11,591 INFO [decode.py:507] averaging ['pruned_transducer_stateless2/exp/epoch-12.pt', 'pruned_transducer_stateless2/exp/epoch-13.pt', 'pruned_transducer_stateless2/exp/epoch-14.pt', 'pruned_transducer_stateless2/exp/epoch-15.pt', 'pruned_transducer_stateless2/exp/epoch-16.pt', 'pruned_transducer_stateless2/exp/epoch-17.pt', 'pruned_transducer_stateless2/exp/epoch-18.pt', 'pruned_transducer_stateless2/exp/epoch-19.pt', 'pruned_transducer_stateless2/exp/epoch-20.pt', 'pruned_transducer_stateless2/exp/epoch-21.pt', 'pruned_transducer_stateless2/exp/epoch-22.pt', 'pruned_transducer_stateless2/exp/epoch-23.pt', 'pruned_transducer_stateless2/exp/epoch-24.pt', 'pruned_transducer_stateless2/exp/epoch-25.pt', 'pruned_transducer_stateless2/exp/epoch-26.pt', 'pruned_transducer_stateless2/exp/epoch-27.pt', 'pruned_transducer_stateless2/exp/epoch-28.pt', 'pruned_transducer_stateless2/exp/epoch-29.pt']
+2022-05-31 17:23:42,322 INFO [decode.py:521] Number of model parameters: 84427758
+2022-05-31 17:23:42,326 INFO [asr_datamodule.py:339] About to create dev dataset
+2022-05-31 17:23:44,785 INFO [asr_datamodule.py:358] About to create dev dataloader
+2022-05-31 17:23:56,217 INFO [decode.py:392] batch 0/?, cuts processed until now is 25
+2022-05-31 17:26:14,481 INFO [decode.py:392] batch 50/?, cuts processed until now is 2298
+2022-05-31 17:27:44,249 INFO [decode.py:409] The transcripts are stored in pruned_transducer_stateless2/exp/modified_beam_search/recogs-dev-beam_size_4-epoch-29-avg-18-beam-4.txt
+2022-05-31 17:27:44,430 INFO [utils.py:406] [dev-beam_size_4] %WER 30.38% [26376 / 86810, 2798 ins, 8387 del, 15191 sub ]
+2022-05-31 17:27:44,946 INFO [decode.py:422] Wrote detailed error stats to pruned_transducer_stateless2/exp/modified_beam_search/errs-dev-beam_size_4-epoch-29-avg-18-beam-4.txt
+2022-05-31 17:27:44,947 INFO [decode.py:439] 
+For dev, WER of different settings are:
+beam_size_4	30.38	best for dev
+
+2022-05-31 17:27:52,462 INFO [decode.py:392] batch 0/?, cuts processed until now is 27
+2022-05-31 17:30:10,576 INFO [decode.py:392] batch 50/?, cuts processed until now is 2294
+2022-05-31 17:32:28,880 INFO [decode.py:392] batch 100/?, cuts processed until now is 4668
+2022-05-31 17:34:40,058 INFO [decode.py:392] batch 150/?, cuts processed until now is 6964
+2022-05-31 17:36:43,391 INFO [decode.py:392] batch 200/?, cuts processed until now is 10119
+2022-05-31 17:37:20,885 INFO [decode.py:409] The transcripts are stored in pruned_transducer_stateless2/exp/modified_beam_search/recogs-test-beam_size_4-epoch-29-avg-18-beam-4.txt
+2022-05-31 17:37:21,336 INFO [utils.py:406] [test-beam_size_4] %WER 33.02% [74695 / 226178, 6881 ins, 26184 del, 41630 sub ]
+2022-05-31 17:37:22,663 INFO [decode.py:422] Wrote detailed error stats to pruned_transducer_stateless2/exp/modified_beam_search/errs-test-beam_size_4-epoch-29-avg-18-beam-4.txt
+2022-05-31 17:37:22,664 INFO [decode.py:439] 
+For test, WER of different settings are:
+beam_size_4	33.02	best for test
+
+2022-05-31 17:37:22,664 INFO [decode.py:602] Done!

log/modified_beam_search/wer-summary-dev-beam_size_4-epoch-29-avg-18-beam-4.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_size_4	30.38

log/modified_beam_search/wer-summary-test-beam_size_4-epoch-29-avg-18-beam-4.txt

@@ -0,0 +1,2 @@
+settings	WER
+beam_size_4	33.02

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test_wavs/RESULTS.md

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+(k2-python) luomingshuang@de-74279-k2-train-1-0307195509-54c966b95f-rtpfq:~/codes/icefall-pruned-rnnt2-ali-meeting/egs/alimeeting/ASR$ CUDA_VISIBLE_DEVICES='' python pruned_transducer_stateless2/pretrained.py --checkpoint pruned_transducer_stateless2/exp/pretrained_epoch_29_avg_18.pt --decoding-method greedy_search --lang-dir data/lang_char icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg0.wav icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg1.wav icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg2.wav
+2022-06-01 13:02:03,906 INFO [lexicon.py:176] Loading pre-compiled data/lang_char/Linv.pt
+2022-06-01 13:02:03,927 INFO [pretrained.py:218] {'best_train_loss': inf, 'best_valid_loss': inf, 'best_train_epoch': -1, 'best_valid_epoch': -1, 'batch_idx_train': 10, 'log_interval': 1, 'reset_interval': 200, 'valid_interval': 400, 'feature_dim': 80, 'subsampling_factor': 4, 'encoder_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'decoder_dim': 512, 'joiner_dim': 512, 'model_warm_step': 200, 'env_info': {'k2-version': '1.15.1', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f8d2dba06c000ffee36aab5b66f24e7c9809f116', 'k2-git-date': 'Thu Apr 21 12:20:34 2022', 'lhotse-version': '1.2.0.dev+git.de75634.dirty', 'torch-version': '1.11.0', 'torch-cuda-available': False, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'pruned-rnnt2-ali-meeting', 'icefall-git-sha1': '5e507f3-dirty', 'icefall-git-date': 'Fri May 20 01:47:19 2022', 'icefall-path': '/ceph-meixu/luomingshuang/icefall', 'k2-path': '/ceph-ms/luomingshuang/k2_latest/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-meixu/luomingshuang/anaconda3/envs/k2-python/lib/python3.8/site-packages/lhotse-1.2.0.dev0+git.de75634.dirty-py3.8.egg/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-1-0307195509-54c966b95f-rtpfq', 'IP address': '10.177.22.9'}, 'checkpoint': 'pruned_transducer_stateless2/exp/pretrained_epoch_29_avg_18.pt', 'lang_dir': 'data/lang_char', 'decoding_method': 'greedy_search', 'sound_files': ['icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg0.wav', 'icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg1.wav', 'icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg2.wav'], 'sample_rate': 16000, 'beam_size': 4, 'beam': 4, 'max_contexts': 4, 'max_states': 8, 'context_size': 2, 'max_sym_per_frame': 1, 'blank_id': 0, 'vocab_size': 3318}
+2022-06-01 13:02:03,927 INFO [pretrained.py:224] device: cpu
+2022-06-01 13:02:03,927 INFO [pretrained.py:226] Creating model
+2022-06-01 13:02:06,521 INFO [pretrained.py:240] Constructing Fbank computer
+2022-06-01 13:02:06,522 INFO [pretrained.py:250] Reading sound files: ['icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg0.wav', 'icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg1.wav', 'icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg2.wav']
+2022-06-01 13:02:06,610 INFO [pretrained.py:256] Decoding started
+2022-06-01 13:02:10,191 INFO [pretrained.py:273] Using greedy_search
+2022-06-01 13:02:10,927 INFO [pretrained.py:336]
+icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg0.wav:
+啊 行 ， 咱 时 间 也 差 不 多 了 ， 咱 们 今 天 咱 们 公 司 部 门 咱 们 几 个 人 开 个 那 个 部 门 儿 会 ， 然 后 讨 论 一 下 就 是 咱 们 公 司 这 个 办 公 环 境 问 题 啊 ， 我 就 是 。
+
+icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg1.wav:
+咱 们 公 司 成 立 这 么 多 年 了 ， 那 个 想 改 善 一 下 咱 们 员 工 的 这 个 办 这 个 办 公 环 境 ， 还 有 都
+
+icefall_asr_alimeeting_pruned_transducer_stateless2/test_wavs/R8005_M8007_MS806_seg2.wav:
+对 对 大 家 畅 所 欲 言 ， 然 后 那 个 有 什 么 好 的 建 议 啊 什 么 想 法 儿 啊 ， 大 家 都 可 以 提 ， 然 后 咱 们 先 说 咱 们 那 个 办 公 环 境 目 前 咱 们 有 什 么 不 足 ， 然 后 需 要 在 哪 方 面 儿 改 善 一 下 哎 。
+
+
+2022-06-01 13:02:10,927 INFO [pretrained.py:338] Decoding Done