* pruned-transducer-stateless5 recipe for aishell4
* pruned-transducer-stateless5 recipe for aishell4
* do some changes and text normalize
* do some changes
* add text normalize
* combine the training data and decode without webdataset
* update codes for merging
* Do a change for READMD.md
* copy files from existing branch
* add rule in .flake8
* monir style fix
* fix typos
* add tail padding
* refactor, use fixed-length cache for batch decoding
* copy from streaming branch
* copy from streaming branch
* modify emformer states stack and unstack, streaming decoding, to be continued
* refactor Stream class
* remane streaming_feature_extractor.py
* refactor streaming decoding
* test states stack and unstack
* fix bugs, no grad, and num_proccessed_frames
* add modify_beam_search, fast_beam_search
* support torch.jit.export
* use torch.div
* copy from pruned_transducer_stateless4
* modify export.py
* add author info
* delete other test functions
* minor fix
* modify doc
* fix style
* minor fix doc
* minor fix
* minor fix doc
* update RESULTS.md
* fix typo
* add info
* fix typo
* fix doc
* add test function for conv module, and minor fix.
* add copyright info
* minor change of test_emformer.py
* fix doc of stack and unstack, test case with batch_size=1
* update README.md
* Use jsonl for cutsets in the librispeech recipe.
* Use lazy cutset for all recipes.
* More fixes to use lazy CutSet.
* Remove force=True from logging to support Python < 3.8
* Minor fixes.
* Fix style issues.
* update RESULT.md about pruned_transducer_stateless4
* Update RESULT.md
This PR is only to update RESULT.md about pruned_transducer_stateless4.
* set default value of --use-averaged-model to True
* update RESULTS.md and add decode command
* minor fix
* update export.py
* add uploaded files links
* update link
* fix typos
* add pruned-rnnt2 recipe for alimeeting dataset
* update code for merging
* change LilcomHdf5Writer to ChunkedLilcomHdf5Writer
* change for test.yml
* change for test.yml
* change for test.yml
* change for workflow yml
* change for yml
* change for yml
* change for README.md
* change for yml
* solve the conflicts
* solve the conflicts
* add char-based pruned-rnnt2 for wenetspeech
* style check
* style check
* change for export.py
* do some changes
* do some changes
* a small change for .flake8
* solve the conflicts
* Copy files for editing.
* Add random combine from #229.
* Minor fixes.
* Pass model parameters from the command line.
* Fix warnings.
* Fix warnings.
* Update readme.
* Rename to avoid conflicts.
* Update results.
* Add CI for pruned_transducer_stateless5
* Typo fixes.
* Remove random combiner.
* Update decode.py and train.py to use periodically averaged models.
* Minor fixes.
* Revert to use random combiner.
* Update results.
* Minor fixes.
* keep model_avg on cpu
* explicitly convert model_avg to cpu
* minor fix
* remove device convertion for model_avg
* modify usage of the model device in train.py
* change model.device to next(model.parameters()).device for decoding
* assert params.start_epoch>0
* assert params.start_epoch>0, params.start_epoch
* First upload of model average codes.
* minor fix
* update decode file
* update .flake8
* rename pruned_transducer_stateless3 to pruned_transducer_stateless4
* change epoch number counter starting from 1 instead of 0
* minor fix of pruned_transducer_stateless4/train.py
* refactor the checkpoint.py
* minor fix, update docs, and modify the epoch number to count from 1 in the pruned_transducer_stateless4/decode.py
* update author info
* add docs of the scaling in function average_checkpoints_with_averaged_model
* Copy files for editing.
* Use librispeech + gigaspeech with modified conformer.
* Support specifying number of workers for on-the-fly feature extraction.
* Feature extraction code for GigaSpeech.
* Combine XL splits lazily during training.
* Fix warnings in decoding.
* Add decoding code for GigaSpeech.
* Fix decoding the gigaspeech dataset.
We have to use the decoder/joiner networks for the GigaSpeech dataset.
* Disable speed perturbe for XL subset.
* Compute the Nbest oracle WER for RNN-T decoding.
* Minor fixes.
* Minor fixes.
* Add results.
* Update results.
* Update CI.
* Update results.
* Fix style issues.
* Update results.
* Fix style issues.
