## Results ### TAL_CSASR Mix Chars and BPEs training results (Pruned Transducer Stateless5) #### 2022-06-22 Using the codes from this PR https://github.com/k2-fsa/icefall/pull/428. The WERs are |decoding-method | epoch(iter) | avg | dev | test | |--|--|--|--|--| |greedy_search | 30 | 24 | 7.49 | 7.58| |modified_beam_search | 30 | 24 | 7.33 | 7.38| |fast_beam_search | 30 | 24 | 7.32 | 7.42| |greedy_search(use-averaged-model=True) | 30 | 24 | 7.30 | 7.39| |modified_beam_search(use-averaged-model=True) | 30 | 24 | 7.15 | 7.22| |fast_beam_search(use-averaged-model=True) | 30 | 24 | 7.18 | 7.27| |greedy_search | 348000 | 30 | 7.46 | 7.54| |modified_beam_search | 348000 | 30 | 7.24 | 7.36| |fast_beam_search | 348000 | 30 | 7.25 | 7.39 | The results (CER(%) and WER(%)) for Chinese CER and English WER respectivly (zh: Chinese, en: English): |decoding-method | epoch(iter) | avg | dev | dev_zh | dev_en | test | test_zh | test_en | |--|--|--|--|--|--|--|--|--| |greedy_search(use-averaged-model=True) | 30 | 24 | 7.30 | 6.48 | 19.19 |7.39| 6.66 | 19.13| |modified_beam_search(use-averaged-model=True) | 30 | 24 | 7.15 | 6.35 | 18.95 | 7.22| 6.50 | 18.70 | |fast_beam_search(use-averaged-model=True) | 30 | 24 | 7.18 | 6.39| 18.90 | 7.27| 6.55 | 18.77| The training command for reproducing is given below: ``` export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5" ./pruned_transducer_stateless5/train.py \ --world-size 6 \ --num-epochs 30 \ --start-epoch 1 \ --exp-dir pruned_transducer_stateless5/exp \ --lang-dir data/lang_char \ --max-duration 90 ``` The tensorboard training log can be found at https://tensorboard.dev/experiment/KaACzXOVR0OM6cy0qbN5hw/#scalars The decoding command is: ``` epoch=30 avg=24 use_average_model=True ## greedy search ./pruned_transducer_stateless5/decode.py \ --epoch $epoch \ --avg $avg \ --exp-dir pruned_transducer_stateless5/exp \ --lang-dir ./data/lang_char \ --max-duration 800 \ --use-averaged-model $use_average_model ## modified beam search ./pruned_transducer_stateless5/decode.py \ --epoch $epoch \ --avg $avg \ --exp-dir pruned_transducer_stateless5/exp \ --lang-dir ./data/lang_char \ --max-duration 800 \ --decoding-method modified_beam_search \ --beam-size 4 \ --use-averaged-model $use_average_model ## fast beam search ./pruned_transducer_stateless5/decode.py \ --epoch $epoch \ --avg $avg \ --exp-dir ./pruned_transducer_stateless5/exp \ --lang-dir ./data/lang_char \ --max-duration 1500 \ --decoding-method fast_beam_search \ --beam 4 \ --max-contexts 4 \ --max-states 8 \ --use-averaged-model $use_average_model ``` A pre-trained model and decoding logs can be found at