fix recipe train and avg shell

examples/aishell/s0/local/client.sh

@@ -1,20 +0,0 @@
-#!/bin/bash
-
-source path.sh
-
-# run on MacOS
-# brew install portaudio
-# pip install pyaudio
-# pip install keyboard
-
-# start demo client
-python3 -u ${BIN_DIR}/deploy/client.py \
---host_ip="localhost" \
---host_port=8086 \
-
-if [ $? -ne 0 ]; then
-    echo "Failed in starting demo client!"
-    exit 1
-fi
-
-exit 0

examples/aishell/s0/local/server.sh

@@ -1,40 +0,0 @@
-#!/bin/bash
-# TODO: replace the model with a mandarin model
-
-if [[ $# != 1 ]];then
-   echo "usage: $1 checkpoint_path"
-   exit -1
-fi
-
-source path.sh
-
-# download language model
-bash local/download_lm_ch.sh
-if [ $? -ne 0 ]; then
-    exit 1
-fi
-
-# download well-trained model
-#bash local/download_model.sh
-#if [ $? -ne 0 ]; then
-#    exit 1
-#fi
-
-# start demo server
-CUDA_VISIBLE_DEVICES=0 \
-python3 -u ${BIN_DIR}/deploy/server.py \
---device 'gpu' \
---nproc 1 \
---config conf/deepspeech2.yaml \
---host_ip="localhost" \
---host_port=8086 \
---speech_save_dir="demo_cache" \
---checkpoint_path ${1}
-
-if [ $? -ne 0 ]; then
-    echo "Failed in starting demo server!"
-    exit 1
-fi
-
-
-exit 0

examples/aishell/s0/local/train.sh

@@ -20,7 +20,7 @@ fi
 mkdir -p exp
 
 seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -32,7 +32,7 @@ python3 -u ${BIN_DIR}/train.py \
 --model_type ${model_type} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/aishell/s0/local/tune.sh

@@ -1,28 +0,0 @@
-#!/bin/bash
-
-# grid-search for hyper-parameters in language model
-python3 -u ${BIN_DIR}/tune.py \
---device 'gpu' \
---nproc 1 \
---config conf/deepspeech2.yaml \
---num_batches=10 \
---batch_size=128 \
---beam_size=300 \
---num_proc_bsearch=8 \
---num_alphas=10 \
---num_betas=10 \
---alpha_from=0.0 \
---alpha_to=5.0 \
---beta_from=-6 \
---beta_to=6 \
---cutoff_prob=1.0 \
---cutoff_top_n=40 \
---checkpoint_path ${1}
-
-if [ $? -ne 0 ]; then
-    echo "Failed in tuning!"
-    exit 1
-fi
-
-
-exit 0

examples/aishell/s0/run.sh

@@ -27,7 +27,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/aishell/s1/local/train.sh

@@ -19,8 +19,8 @@ echo "using ${device}..."
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -31,7 +31,7 @@ python3 -u ${BIN_DIR}/train.py \
 --output exp/${ckpt_name} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/aishell/s1/run.sh

@@ -25,7 +25,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/callcenter/s1/local/train.sh

@@ -19,8 +19,8 @@ echo "using ${device}..."
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -31,7 +31,7 @@ python3 -u ${BIN_DIR}/train.py \
 --output exp/${ckpt_name} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/callcenter/s1/run.sh

@@ -25,7 +25,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/librispeech/s0/README.md

@@ -1,10 +1,17 @@
 # LibriSpeech
 
+## Data
+| Data Subset | Duration in Seconds |
+| --- | --- |
+| data/manifest.train |  0.83s ~ 29.735s |
+| data/manifest.dev | 1.065 ~ 35.155s |  
+| data/manifest.test-clean | 1.285s ~ 34.955s |
+
 ## Deepspeech2
 
 | Model | Params | release |  Config | Test set | Loss | WER |  
 | --- | --- | --- | --- | --- | --- | --- |  
-| DeepSpeech2 | 42.96M | 2.2.0 | conf/deepspeech2.yaml + spec_aug | 14.49190807 | test-clean | 0.067283 |  
+| DeepSpeech2 | 42.96M | 2.2.0 | conf/deepspeech2.yaml + spec_aug | test-clean | 14.49190807 | 0.067283 |  
-| DeepSpeech2 | 42.96M | 2.1.0 | conf/deepspeech2.yaml | 15.184467315673828 | test-clean | 0.072154 |  
+| DeepSpeech2 | 42.96M | 2.1.0 | conf/deepspeech2.yaml | test-clean | 15.184467315673828 | 0.072154 |  
-| DeepSpeech2 | 42.96M | 2.0.0 | conf/deepspeech2.yaml | - | test-clean | 0.073973 |  
+| DeepSpeech2 | 42.96M | 2.0.0 | conf/deepspeech2.yaml | test-clean | - | 0.073973 |  
 | DeepSpeech2 | 42.96M | 1.8.5 | - | test-clean | - | 0.074939 |  

examples/librispeech/s0/local/train.sh

@@ -20,8 +20,8 @@ echo "using ${device}..."
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -33,7 +33,7 @@ python3 -u ${BIN_DIR}/train.py \
 --model_type ${model_type} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/librispeech/s0/local/tune.sh

@@ -1,33 +0,0 @@
-#!/bin/bash
-
-if [ $# != 1 ];then
-    echo "usage: tune ckpt_path"
-    exit 1
-fi
-
-# grid-search for hyper-parameters in language model
-python3 -u ${BIN_DIR}/tune.py \
---device 'gpu' \
---nproc 1 \
---config conf/deepspeech2.yaml \
---num_batches=-1 \
---batch_size=128 \
---beam_size=500 \
---num_proc_bsearch=12 \
---num_alphas=45 \
---num_betas=8 \
---alpha_from=1.0 \
---alpha_to=3.2 \
---beta_from=0.1 \
---beta_to=0.45 \
---cutoff_prob=1.0 \
---cutoff_top_n=40 \
---checkpoint_path ${1}
-
-if [ $? -ne 0 ]; then
-    echo "Failed in tuning!"
-    exit 1
-fi
-
-
-exit 0

examples/librispeech/s0/run.sh

@@ -25,7 +25,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/librispeech/s1/local/train.sh

@@ -19,8 +19,8 @@ echo "using ${device}..."
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -31,7 +31,7 @@ python3 -u ${BIN_DIR}/train.py \
 --output exp/${ckpt_name} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/librispeech/s1/run.sh

@@ -24,7 +24,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/librispeech/s2/local/train.sh

@@ -19,8 +19,8 @@ echo "using ${device}..."
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -32,7 +32,7 @@ python3 -u ${BIN_DIR}/train.py \
 --output exp/${ckpt_name} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/librispeech/s2/run.sh

@@ -25,7 +25,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/punctuation_restoration/README.md

@@ -1,3 +1,3 @@
 # Punctation Restoration
 
-Please using `https://github.com/745165806/PaddleSpeechTask` to do this task.
+Please using [PaddleSpeechTask](https://github.com/745165806/PaddleSpeechTask] to do this task.

examples/ted_en_zh/t0/local/train.sh

@@ -19,8 +19,8 @@ echo "using ${device}..."
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -31,7 +31,7 @@ python3 -u ${BIN_DIR}/train.py \
 --output exp/${ckpt_name} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0  ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/ted_en_zh/t0/run.sh

@@ -26,7 +26,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    ../../utils/avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/timit/s1/local/train.sh

@@ -19,8 +19,8 @@ echo "using ${device}..."
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0  ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -31,7 +31,7 @@ python3 -u ${BIN_DIR}/train.py \
 --output exp/${ckpt_name} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/timit/s1/run.sh

@@ -26,7 +26,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/tiny/s0/local/train.sh

@@ -19,8 +19,8 @@ fi
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0  ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -32,7 +32,7 @@ python3 -u ${BIN_DIR}/train.py \
 --model_type ${model_type} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0  ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/tiny/s0/run.sh

@@ -27,7 +27,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then

examples/tiny/s1/local/train.sh

@@ -18,8 +18,8 @@ fi
 
 mkdir -p exp
 
-seed=1024
+seed=10086
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     export FLAGS_cudnn_deterministic=True
 fi
 
@@ -30,7 +30,7 @@ python3 -u ${BIN_DIR}/train.py \
 --output exp/${ckpt_name} \
 --seed ${seed}
 
-if [ ${seed} ]; then
+if [ ${seed} != 0 ]; then
     unset FLAGS_cudnn_deterministic
 fi
 

examples/tiny/s1/run.sh

@@ -25,7 +25,7 @@ fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
     # avg n best model
-    avg.sh exp/${ckpt}/checkpoints ${avg_num}
+    avg.sh best exp/${ckpt}/checkpoints ${avg_num}
 fi
 
 if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then