7 Commits

Author SHA1 Message Date
Fangjun Kuang
3effcb4225
Fix typos. (#85) 2021-10-18 16:17:14 +08:00
Fangjun Kuang
53b79fafa7
Add MMI training with word pieces as modelling unit. (#6)
* Fix an error in TDNN-LSTM training.

* WIP: Refactoring

* Refactor transformer.py

* Remove unused code.

* Minor fixes.

* Fix decoder padding mask.

* Add MMI training with word pieces.

* Remove unused files.

* Minor fixes.

* Refactoring.

* Minor fixes.

* Use pre-computed alignments in LF-MMI training.

* Minor fixes.

* Update decoding script.

* Add doc about how to check and use extracted alignments.

* Fix style issues.

* Fix typos.

* Fix style issues.

* Disable macOS tests for now.
2021-10-18 15:20:32 +08:00
Fangjun Kuang
4890e27b45
Extract framewise alignment information using CTC decoding (#39)
* Use new APIs with k2.RaggedTensor

* Fix style issues.

* Update the installation doc, saying it requires at least k2 v1.7

* Extract framewise alignment information using CTC decoding.

* Print environment information.

Print information about k2, lhotse, PyTorch, and icefall.

* Fix CI.

* Fix CI.

* Compute framewise alignment information of the LibriSpeech dataset.

* Update comments for the time to compute alignments of train-960.

* Preserve cut id in mix cut transformer.

* Minor fixes.

* Add doc about how to extract framewise alignments.
2021-10-18 14:24:33 +08:00
pkufool
f4223ee110
Add TDNN-LSTM-CTC Results (#25)
* Add tdnn-lstm pretrained model and results

* Add docs for TDNN-LSTM-CTC

* Minor fix

* Fix typo

* Fix style checking
2021-08-24 21:09:27 +08:00
Fangjun Kuang
1bd5dcc8ac
WIP: Add doc for the LibriSpeech recipe. (#24)
* WIP: Add doc for the LibriSpeech recipe.

* Add more doc for LibriSpeech recipe.

* Add more doc for the LibriSpeech recipe.

* More doc.
2021-08-24 20:28:32 +08:00
Fangjun Kuang
0b656e4e1c
Add a link to Colab. (#14)
It demonstrates the usages of pre-trained models.
2021-08-20 15:43:25 +08:00
Fangjun Kuang
9d0cc9d829
Support computing nbest oracle WER. (#10)
* Support computing nbest oracle WER.

* Add scale to all nbest based decoding/rescoring methods.

* Add script to run pretrained models.

* Use torchaudio to extract features.

* Support decoding multiple files at the same time.

Also, use kaldifeat for feature extraction.

* Support decoding with LM rescoring and attention-decoder rescoring.

* Minor fixes.

* Replace scale with lattice-score-scale.

* Add usage example with a provided pretrained model.
2021-08-20 11:53:37 +08:00