mirrors/icefall
1
0
Fork 0
mirror of https://github.com/k2-fsa/icefall.git synced 2025-08-08 09:32:20 +00:00
Code Issues Packages Projects Releases Wiki Activity
icefall/egs/wenetspeech/ASR
History
Li Peng 3e4da5f781
Replace deprecated pytorch methods (#1814) 
* Replace deprecated pytorch methods

- torch.cuda.amp.GradScaler(...) => torch.amp.GradScaler("cuda", ...)
- torch.cuda.amp.autocast(...) => torch.amp.autocast("cuda", ...)

* Replace `with autocast(...)` with `with autocast("cuda", ...)`


Co-authored-by: Li Peng <lipeng@unisound.ai>
2024-12-16 10:24:16 +08:00
..
local
update speechio whisper ft results (#1605)
2024-04-30 11:49:20 +08:00
pruned_transducer_stateless2
Replace deprecated pytorch methods (#1814)
2024-12-16 10:24:16 +08:00
pruned_transducer_stateless5
Replace deprecated pytorch methods (#1814)
2024-12-16 10:24:16 +08:00
whisper
Replace deprecated pytorch methods (#1814)
2024-12-16 10:24:16 +08:00
zipformer
Replace deprecated pytorch methods (#1814)
2024-12-16 10:24:16 +08:00
finetune.sh
Add finetuning script for aishell (#974)
2023-03-30 17:08:46 +08:00
prepare.sh
fix the fixed num_splits (#1772)
2024-10-16 17:19:24 +08:00
README.md
[WIP] Pruned-transducer-stateless5-for-WenetSpeech (offline and streaming) (#447)
2022-07-28 12:54:27 +08:00
RESULTS.md
zipformer wenetspeech (#1130)
2023-06-26 09:33:18 +08:00
shared
[Ready to merge] Pruned Transducer Stateless2 for WenetSpeech (char-based) (#349)
2022-05-23 17:13:01 +08:00

README.md

Introduction

This recipe includes some different ASR models trained with WenetSpeech.

./RESULTS.md contains the latest results.

Transducers

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

Encoder Decoder Comment
pruned_transducer_stateless2 Conformer(modified) Embedding + Conv1d Using k2 pruned RNN-T loss
pruned_transducer_stateless5 Conformer(modified) 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.