* initial commit for zipformer tedlium
* fix unk decoding
* add pretrained model and logs
* update for new AsrModel
* add option for choosing rnnt type
* add results with modified rnnt
* copy files
* update train.py
* small fixes
* Add decode.py
* Fix dataloader in decode.py
* add blank penalty
* Add blank-penalty to other decoding method
* Minor fixes
* add zipformer2 recipe
* Minor fixes
* Remove pruned7
* export and test models
* Replace bpe with tokens in export.py and pretrain.py
* Minor fixes
* Minor fixes
* Minor fixes
* Fix export
* Update results
* Fix zipformer-ctc
* Fix ci
* Fix ci
* Fix CI
* Fix CI
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Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>
* add CTC loss option in zipformer recipe
* add ctc_decode.py
* support CTC model export, add jit_pretrained_ctc.py, pretrained_ctc.py
* update README.md and RESULTS.md
* add CI test
* copy files from zipformer librispeech
* Add byte bpe training for aishell
* compile LG graph
* Support LG decoding
* Minor fixes
* black
* Minor fixes
* export & fix pretrain.py
* fix black
* Update RESULTS.md
* Fix export.py
* support transformer LM
* show number of parameters during training
* update docstring
* testing files for ppl calculation
* add lm wrampper for rnn and transformer LM
* apply lm wrapper in lm shallow fusion
* small updates
* update decode.py to support LM fusion and LODR
* add export.py
* update CI and workflow
* update decoding results
* fix CI
* remove transformer LM from CI test
* print out timestamps during decoding
* add word-level alignments
* support to compute mean symbol delay with word-level alignments
* print variance of symbol delay
* update doc
* support to compute delay for pruned_transducer_stateless4
* fix bug
* add doc
* Add utility for shallow fusion
* test batch size == 1 without shallow fusion
* Use shallow fusion for modified-beam-search
* Modified beam search with ngram rescoring
* Fix code according to review
Co-authored-by: Fangjun Kuang <csukuangfj@gmail.com>
* Add fast_beam_search_nbest.
* Fix CI errors.
* Fix CI errors.
* More fixes.
* Small fixes.
* Support using log_add in LG decoding with fast_beam_search.
* Support LG decoding in pruned_transducer_stateless
* Support LG for pruned_transducer_stateless2.
* Support LG for fast beam search.
* Minor fixes.
* 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
* 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
* 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.
