fix wav2vec2 test_wav.sh run error.

examples/aishell/asr3/README.md

@@ -190,9 +190,9 @@ tar xzvf wav2vec2ASR-large-aishell1_ckpt_1.4.0.model.tar.gz
 ```
 You can download the audio demo:
 ```bash
-wget -nc https://paddlespeech.bj.bcebos.com/datasets/single_wav/en/demo_002_en.wav -P data/
+wget -nc https://paddlespeech.bj.bcebos.com/datasets/single_wav/zh/demo_01_03.wav -P data/
 ```
 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
-CUDA_VISIBLE_DEVICES= ./local/test_wav.sh conf/wav2vec2ASR.yaml conf/tuning/decode.yaml exp/wav2vec2ASR/checkpoints/avg_1 data/demo_002_en.wav
+CUDA_VISIBLE_DEVICES= ./local/test_wav.sh conf/wav2vec2ASR.yaml conf/tuning/decode.yaml exp/wav2vec2ASR/checkpoints/avg_1 data/demo_01_03.wav
 ```

examples/aishell/asr3/conf/wav2vec2ASR.yaml

@@ -107,6 +107,7 @@ vocab_filepath: data/lang_char/vocab.txt
 ###########################################
 
 unit_type: 'char'
+tokenizer: bert-base-chinese
 mean_std_filepath: 
 preprocess_config: conf/preprocess.yaml
 sortagrad: -1 # Feed samples from shortest to longest ; -1: enabled for all epochs, 0: disabled, other: enabled for 'other' epochs 
@@ -163,3 +164,4 @@ log_interval: 1
 checkpoint:
   kbest_n: 50
   latest_n: 5
+

examples/aishell/asr3/local/test.sh

@@ -8,9 +8,7 @@ echo "using $ngpu gpus..."
 expdir=exp
 datadir=data
 
-train_set=train_960
-recog_set="test-clean test-other dev-clean dev-other"
-recog_set="test-clean"
+train_set=train
 
 config_path=$1
 decode_config_path=$2
@@ -75,7 +73,7 @@ for type in ctc_prefix_beam_search; do
         --trans_hyp ${ckpt_prefix}.${type}.rsl.text
 
     python3 utils/compute-wer.py --char=1 --v=1 \
-        data/manifest.test-clean.text ${ckpt_prefix}.${type}.rsl.text > ${ckpt_prefix}.${type}.error
+        data/manifest.test.text ${ckpt_prefix}.${type}.rsl.text > ${ckpt_prefix}.${type}.error
     echo "decoding ${type} done."
 done
 

examples/aishell/asr3/local/test_wav.sh

@@ -14,7 +14,7 @@ ckpt_prefix=$3
 audio_file=$4
 
 mkdir -p data
-wget -nc https://paddlespeech.bj.bcebos.com/datasets/single_wav/en/demo_002_en.wav -P data/
+wget -nc https://paddlespeech.bj.bcebos.com/datasets/single_wav/zh/demo_01_03.wav -P data/
 if [ $? -ne 0 ]; then
    exit 1
 fi

examples/aishell/asr3/run.sh

@@ -15,7 +15,7 @@ resume=         # xx e.g. 30
 export FLAGS_cudnn_deterministic=1
 . ${MAIN_ROOT}/utils/parse_options.sh || exit 1;
 
-audio_file=data/demo_002_en.wav
+audio_file=data/demo_01_03.wav
 
 avg_ckpt=avg_${avg_num}
 ckpt=$(basename ${conf_path} | awk -F'.' '{print $1}')

paddlespeech/resource/pretrained_models.py

@@ -102,13 +102,11 @@ ssl_dynamic_pretrained_models = {
             'params':
             'exp/wav2vec2ASR/checkpoints/avg_1.pdparams',
         },
-    },
-    "wav2vec2ASR_aishell1-zh-16k": {
         '1.4': {
             'url':
             'https://paddlespeech.bj.bcebos.com/s2t/aishell/asr3/wav2vec2ASR-large-aishell1_ckpt_1.4.0.model.tar.gz',
             'md5':
-            '9f0bc943adb822789bf61e674b229d17',
+            '150e51b8ea5d255ccce6b395de8d916a',
             'cfg_path':
             'model.yaml',
             'ckpt_path':

paddlespeech/s2t/exps/wav2vec2/bin/test_wav.py

@@ -18,6 +18,7 @@ from pathlib import Path
 
 import paddle
 import soundfile
+from paddlenlp.transformers import AutoTokenizer
 from yacs.config import CfgNode
 
 from paddlespeech.s2t.frontend.featurizer.text_featurizer import TextFeaturizer
@@ -34,8 +35,13 @@ class Wav2vec2Infer():
         self.config = config
         self.audio_file = args.audio_file
 
-        self.text_feature = TextFeaturizer(
-            unit_type=config.unit_type, vocab=config.vocab_filepath)
+        if self.config.tokenizer:
+            self.text_feature = AutoTokenizer.from_pretrained(
+                self.config.tokenizer)
+        else:
+            self.text_feature = TextFeaturizer(
+                unit_type=config.unit_type, vocab=config.vocab_filepath)
+
         paddle.set_device('gpu' if self.args.ngpu > 0 else 'cpu')
 
         # model
@@ -59,14 +65,14 @@ class Wav2vec2Infer():
             audio, _ = soundfile.read(
                 self.audio_file, dtype="int16", always_2d=True)
             logger.info(f"audio shape: {audio.shape}")
-
             xs = paddle.to_tensor(audio, dtype='float32').unsqueeze(axis=0)
             decode_config = self.config.decode
             result_transcripts, result_tokenids = self.model.decode(
                 xs,
                 text_feature=self.text_feature,
                 decoding_method=decode_config.decoding_method,
-                beam_size=decode_config.beam_size)
+                beam_size=decode_config.beam_size,
+                tokenizer=self.config.tokenizer, )
             rsl = result_transcripts[0]
             utt = Path(self.audio_file).name
             logger.info(f"hyp: {utt} {rsl}")