Fangjun Kuang f23dd43719

Update results for libri+giga multi dataset setup. (#363) ...

* Update results for libri+giga multi dataset setup.

2022-05-14 21:45:39 +08:00

..

__init__.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00

asr_datamodule.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00

beam_search.py

Ignore padding frames during RNN-T decoding. (#358)

2022-05-13 07:39:14 +08:00

conformer.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00

decode.py

Ignore padding frames during RNN-T decoding. (#358)

2022-05-13 07:39:14 +08:00

decoder.py

Tedlium3 pruned transducer stateless (#261)

2022-04-11 17:08:53 +08:00

encoder_interface.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00

export.py

Add modified beam search for pruned rnn-t. (#248)

2022-03-12 16:16:55 +08:00

joiner.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00

model.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00

pretrained.py

Update results for libri+giga multi dataset setup. (#363)

2022-05-14 21:45:39 +08:00

subsampling.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00

test_decoder.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00

train.py

Support computing RNN-T loss with torchaudio (#316)

2022-04-19 18:47:13 +08:00

transformer.py

Use k2 pruned transducer loss to train conformer-transducer model (#194)

2022-02-17 13:33:54 +08:00