* Add modified beam search for pruned rnn-t.
* Fix style issues.
* Update RESULTS.md.
* Fix typos.
* Minor fixes.
* Test the pre-trained model using GitHub actions.
* Let the user install optimized_transducer on her own.
* Fix errors in GitHub CI.
* Add force alignment for stateless transducer.
* Add more documentation.
* Compute word starting time from framewise token alignment.
* Update README to include force alignment information.
* Fix typos.
* Fix more typos.
* Fixes after review.
* Adding diagnostics code...
* Move diagnostics code from local dir to the shared icefall dir
* Remove the diagnostics code in the local dir
* Update docs of arguments, and remove stats_types() function in TensorDiagnosticOptions object.
* Update docs of arguments.
* Add copyright information.
* Corrected the time in copyright information.
Co-authored-by: Daniel Povey <dpovey@gmail.com>
* Add modified transducer for aishell.
* Minor fixes.
* Add extra data in transducer training.
The extra data is from http://www.openslr.org/62/
* Update export.py and pretrained.py
* Update CI to install pretrained models with aishell.
* Update results.
* Update results.
* Update README.
* Use symlinks to avoid copies.
* Begin to use multiple datasets.
* Finish preparing training datasets.
* Minor fixes
* Copy files.
* Finish training code.
* Display losses for gigaspeech and librispeech separately.
* Fix decode.py
* Make the probability to select a batch from GigaSpeech configurable.
* Update results.
* Minor fixes.
* Disable weight decay.
* Remove input feature batchnorm..
* Replace BatchNorm in the Conformer model with LayerNorm.
* Use tanh in the joint network.
* Remove sos ID.
* Reduce the number of decoder layers from 4 to 2.
* Minor fixes.
* Fix typos.
* Begin to add RNN-T training for librispeech.
* Copy files from conformer_ctc.
Will edit it.
* Use conformer/transformer model as encoder.
* Begin to add training script.
* Add training code.
* Remove long utterances to avoid OOM when a large max_duraiton is used.
* Begin to add decoding script.
* Add decoding script.
* Minor fixes.
* Add beam search.
* Use LSTM layers for the encoder.
Need more tunings.
* Use stateless decoder.
* Minor fixes to make it ready for merge.
* Fix README.
* Update RESULT.md to include RNN-T Conformer.
* Minor fixes.
* Fix tests.
* Minor fixes.
* Minor fixes.
* Fix tests.
* Apply layer normalization to the output of each gate in LSTM.
* Apply layer normalization to the output of each gate in GRU.
* Add projection support to LayerNormLSTMCell.
* Add GPU tests.
* Use typeguard.check_argument_types() to validate type annotations.
* Add typeguard as a requirement.
* Minor fixes.
* Fix CI.
* Fix CI.
* Fix test failures for torch 1.8.0
* Fix errors.
We are using multiple machines to do various experiments. It makes
life easier to know which experiment is running on which machine
if we also log the IP and hostname of the machine.
* Modify label smoothing to match the one implemented in PyTorch.
* Enable CI for torch 1.10
* Fix CI errors.
* Fix CI installation errors.
* Fix CI installation errors.
* Minor fixes.
* Minor fixes.
* Minor fixes.
* Minor fixes.
* Minor fixes.
* Fix CI errors.
* Update RESULTS using vocab size 500, att rate 0.8
* Update README.
* Refactoring.
Since FSAs in an Nbest object are linear in structure, we can
add the scores of a path to compute the total scores.
* Update documentation.
* Change default vocab size from 5000 to 500.
