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icefall/egs/librispeech/ASR
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Fangjun Kuang bb7f6ed6b7
Add modified beam search for pruned rnn-t. (#248) 
* 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.
2022-03-12 16:16:55 +08:00
..
conformer_ctc
Reset seed at the beginning of each epoch. (#221)
2022-02-21 15:16:39 +08:00
conformer_mmi
Reset seed at the beginning of each epoch. (#221)
2022-02-21 15:16:39 +08:00
local
Begin to use multiple datasets in training (#213)
2022-02-21 15:27:27 +08:00
pruned_transducer_stateless
Add modified beam search for pruned rnn-t. (#248)
2022-03-12 16:16:55 +08:00
streaming_conformer_ctc
Reset seed at the beginning of each epoch. (#221)
2022-02-21 15:16:39 +08:00
tdnn_lstm_ctc
Add force alignment for stateless transducer. (#239)
2022-03-12 16:16:15 +08:00
transducer
Fix joiner (#234)
2022-03-02 16:41:14 +08:00
transducer_lstm
Reset seed at the beginning of each epoch. (#221)
2022-02-21 15:16:39 +08:00
transducer_stateless
Add force alignment for stateless transducer. (#239)
2022-03-12 16:16:15 +08:00
transducer_stateless_multi_datasets
Fix joiner (#234)
2022-03-02 16:41:14 +08:00
prepare_giga_speech.sh
Begin to use multiple datasets in training (#213)
2022-02-21 15:27:27 +08:00
prepare.sh
Add force alignment for stateless transducer. (#239)
2022-03-12 16:16:15 +08:00
README.md
Add modified beam search for pruned rnn-t. (#248)
2022-03-12 16:16:55 +08:00
RESULTS-100hours.md
Update result for full libri + GigaSpeech using transducer_stateless. (#231)
2022-03-01 17:01:46 +08:00
RESULTS.md
Add modified beam search for pruned rnn-t. (#248)
2022-03-12 16:16:55 +08:00
shared
Refactoring (#4)
2021-08-04 14:53:02 +08:00

README.md

Introduction

Please refer to https://icefall.readthedocs.io/en/latest/recipes/librispeech/index.html for how to run models in this recipe.

Transducers

There are various folders containing the name transducer in this folder. The following table lists the differences among them.

Encoder Decoder Comment
transducer Conformer LSTM
transducer_stateless Conformer Embedding + Conv1d
transducer_lstm LSTM LSTM
transducer_stateless_multi_datasets Conformer Embedding + Conv1d Using data from GigaSpeech as extra training data
pruned_transducer_stateless Conformer Embedding + Conv1d Using k2 pruned RNN-T loss

The decoder in transducer_stateless is modified from the paper Rnn-Transducer with Stateless Prediction Network. We place an additional Conv1d layer right after the input embedding layer.