From 3c93953550d5a8a04382a3cc181370b6da2fe74c Mon Sep 17 00:00:00 2001
From: Jackwaterveg <87408988+Jackwaterveg@users.noreply.github.com>
Date: Fri, 8 Apr 2022 11:23:17 +0800
Subject: [PATCH] test=doc

---
 examples/librispeech/asr2/README.md | 32 +++++------------------------
 1 file changed, 5 insertions(+), 27 deletions(-)

diff --git a/examples/librispeech/asr2/README.md b/examples/librispeech/asr2/README.md
index 7d6fe11d..209a2078 100644
--- a/examples/librispeech/asr2/README.md
+++ b/examples/librispeech/asr2/README.md
@@ -213,17 +213,14 @@ avg.sh latest exp/transformer/checkpoints 10
 ./local/recog.sh  --ckpt_prefix exp/transformer/checkpoints/avg_10
 ```
 ## Pretrained Model
-You can get the pretrained transformer using the scripts below:
-```bash
-# Transformer:
-wget https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr2/transformer.model.tar.gz
-```
+You can get the pretrained models from [this](../../../docs/source/released_model.md).
+
 using the `tar` scripts to unpack the model and then you can use the script to test the model.
 
 For example:
 ```bash
-wget https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr2/transformer.model.tar.gz
-tar xzvf transformer.model.tar.gz
+wget https://paddlespeech.bj.bcebos.com/s2t/librispeech/asr2/asr2_transformer_librispeech_ckpt_0.1.1.model.tar.gz
+tar xzvf asr2_transformer_librispeech_ckpt_0.1.1.model.tar.gz
 source path.sh
 # If you have process the data and get the manifest file， you can skip the following 2 steps
 bash local/data.sh --stage -1 --stop_stage -1
@@ -231,26 +228,7 @@ bash local/data.sh --stage 2 --stop_stage 2
 
 CUDA_VISIBLE_DEVICES= ./local/test.sh conf/transformer.yaml exp/ctc/checkpoints/avg_10
 ```
-The performance of the released models are shown below:
-### Transformer
-|    Model    | Params |          GPUS          |  Averaged Model  |        Config         | Augmentation |      Loss       |
-| :---------: | :----: | :--------------------: | :--------------: | :-------------------: | :----------: | :-------------: |
-| transformer | 32.52M | 8 Tesla V100-SXM2-32GB | 10-best val_loss | conf/transformer.yaml |   spec_aug   | 6.3197922706604 |
-
-#### Attention Rescore
-| Test Set   | Decode Method         | #Snt | #Wrd  | Corr | Sub  | Del  | Ins  | Err  | S.Err |
-| ---------- | --------------------- | ---- | ----- | ---- | ---- | ---- | ---- | ---- | ----- |
-| test-clean | attention             | 2620 | 52576 | 96.4 | 2.5  | 1.1  | 0.4  | 4.0  | 34.7  |
-| test-clean | ctc_greedy_search     | 2620 | 52576 | 95.9 | 3.7  | 0.4  | 0.5  | 4.6  | 48.0  |
-| test-clean | ctc_prefix_beamsearch | 2620 | 52576 | 95.9 | 3.7  | 0.4  | 0.5  | 4.6  | 47.6  |
-| test-clean | attention_rescore     | 2620 | 52576 | 96.8 | 2.9  | 0.3  | 0.4  | 3.7  | 38.0  |
-
-#### JoinCTC
-| Test Set   | Decode Method     | #Snt | #Wrd  | Corr | Sub  | Del  | Ins  | Err  | S.Err |
-| ---------- | ----------------- | ---- | ----- | ---- | ---- | ---- | ---- | ---- | ----- |
-| test-clean | join_ctc_only_att | 2620 | 52576 | 96.1 | 2.5  | 1.4  | 0.4  | 4.4  | 34.7  |
-| test-clean | join_ctc_w/o_lm   | 2620 | 52576 | 97.2 | 2.6  | 0.3  | 0.4  | 3.2  | 34.9  |
-| test-clean | join_ctc_w_lm     | 2620 | 52576 | 97.9 | 1.8  | 0.2  | 0.3  | 2.4  | 27.8  |
+The performance of the released models are shown [here](./RESULTS.md).
 
 Compare with [ESPNET](https://github.com/espnet/espnet/blob/master/egs/librispeech/asr1/RESULTS.md#pytorch-large-transformer-with-specaug-4-gpus--transformer-lm-4-gpus) we using 8gpu, but the model size (aheads4-adim256) small than it.
 ## Stage 5: CTC Alignment