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@ -107,7 +107,7 @@ or you can run these scripts in the command line (only use CPU).
```bash ```bash
source path.sh source path.sh
bash ./local/data.sh bash ./local/data.sh
CUDA_VISIBLE_DEVICES= ./local/train.sh conf/deepspeech2.yaml deepspeech2 CUDA_VISIBLE_DEVICES= ./local/train.sh conf/deepspeech2.yaml deepspeech2
``` ```
## Stage 2: Top-k Models Averaging ## Stage 2: Top-k Models Averaging
After training the model, we need to get the final model for testing and inference. In every epoch, the model checkpoint is saved, so we can choose the best model from them based on the validation loss or we can sort them and average the parameters of the top-k models to get the final model. We can use stage 2 to do this, and the code is shown below: After training the model, we need to get the final model for testing and inference. In every epoch, the model checkpoint is saved, so we can choose the best model from them based on the validation loss or we can sort them and average the parameters of the top-k models to get the final model. We can use stage 2 to do this, and the code is shown below:
@ -157,14 +157,14 @@ using the `tar` scripts to unpack the model and then you can use the script to t
For example: For example:
``` ```
wget https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_aishell_ckpt_0.1.1.model.tar.gz wget https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_offline_aishell_ckpt_1.0.1.model.tar.gz
tar xzvf asr0_deepspeech2_aishell_ckpt_0.1.1.model.tar.gz tar xzvf asr0_deepspeech2_offline_aishell_ckpt_1.0.1.model.tar.gz
source path.sh source path.sh
# If you have process the data and get the manifest file， you can skip the following 2 steps # 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 bash local/data.sh --stage -1 --stop_stage -1
bash local/data.sh --stage 2 --stop_stage 2 bash local/data.sh --stage 2 --stop_stage 2
CUDA_VISIBLE_DEVICES= ./local/test.sh conf/deepspeech2.yaml exp/deepspeech2/checkpoints/avg_1 CUDA_VISIBLE_DEVICES= ./local/test.sh conf/deepspeech2.yaml exp/deepspeech2/checkpoints/avg_10
``` ```
The performance of the released models are shown in [this](./RESULTS.md) The performance of the released models are shown in [this](./RESULTS.md)
## Stage 4: Static graph model Export ## Stage 4: Static graph model Export
@ -178,7 +178,7 @@ This stage is to transform dygraph to static graph.
If you already have a dynamic graph model, you can run this script: If you already have a dynamic graph model, you can run this script:
```bash ```bash
source path.sh source path.sh
./local/export.sh conf/deepspeech2.yaml exp/deepspeech2/checkpoints/avg_10 exp/deepspeech2/checkpoints/avg_10.jit ./local/export.sh conf/deepspeech2.yaml exp/deepspeech2/checkpoints/avg_1 exp/deepspeech2/checkpoints/avg_1.jit
``` ```
## Stage 5: Static graph Model Testing ## Stage 5: Static graph Model Testing
Similar to stage 3, the static graph model can also be tested. Similar to stage 3, the static graph model can also be tested.
@ -202,8 +202,8 @@ if [ ${stage} -le 6 ] && [ ${stop_stage} -ge 6 ]; then
``` ```
you can train the model by yourself, or you can download the pretrained model by the script below: you can train the model by yourself, or you can download the pretrained model by the script below:
```bash ```bash
wget https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_aishell_ckpt_0.1.1.model.tar.gz wget https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_offline_aishell_ckpt_1.0.1.model.tar.gz
tar xzvf asr0_deepspeech2_aishell_ckpt_0.1.1.model.tar.gz tar asr0_deepspeech2_offline_aishell_ckpt_1.0.1.model.tar.gz
``` ```
You can download the audio demo: You can download the audio demo:
```bash ```bash
@ -211,5 +211,5 @@ wget -nc https://paddlespeech.bj.bcebos.com/datasets/single_wav/zh/demo_01_03.wa
``` ```
You need to prepare an audio file or use the audio demo above, please confirm the sample rate of the audio is 16K. You can get the result of the audio demo by running the script below. You need to prepare an audio file or use the audio demo above, please confirm the sample rate of the audio is 16K. You can get the result of the audio demo by running the script below.
```bash ```bash
CUDA_VISIBLE_DEVICES= ./local/test_wav.sh conf/deepspeech2.yaml conf/tuning/decode.yaml exp/deepspeech2/checkpoints/avg_1 data/demo_01_03.wav CUDA_VISIBLE_DEVICES= ./local/test_wav.sh conf/deepspeech2.yaml conf/tuning/decode.yaml exp/deepspeech2/checkpoints/avg_10 data/demo_01_03.wav
``` ```

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