4 Commits

Author	SHA1	Message	Date
Fangjun Kuang	ec591698b0	Associate a cut with token alignment (without repeats) (#125) ... * WIP: Associate a cut with token alignment (without repeats) * Save framewise alignments with/without repeats. * Minor fixes.	2021-11-29 18:50:54 +08:00
Wei Kang	4151cca147	Add torch script support for Aishell and update documents (#124) ... * Add aishell recipe * Remove unnecessary code and update docs * adapt to k2 v1.7, add docs and results * Update conformer ctc model * Update docs, pretrained.py & results * Fix code style * Fix code style * Fix code style * Minor fix * Minor fix * Fix pretrained.py * Update pretrained model & corresponding docs * Export torch script model for Aishell * Add C++ deployment docs * Minor fixes * Fix unit test * Update Readme	2021-11-19 16:37:05 +08:00
Fangjun Kuang	21096e99d8	Update result for the librispeech recipe using vocab size 500 and att rate 0.8 (#113) ... * 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.	2021-11-10 14:32:52 +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