fix u2pp model (#2549)

docs/source/released_model.md

@@ -9,7 +9,7 @@ Acoustic Model | Training Data | Token-based | Size | Descriptions | CER | WER |
 [Ds2 Online Aishell ASR0 Model](https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_online_aishell_fbank161_ckpt_0.2.1.model.tar.gz) | Aishell Dataset | Char-based | 491 MB  | 2 Conv + 5 LSTM layers | 0.0666 |-| 151 h | [D2 Online Aishell ASR0](../../examples/aishell/asr0) | onnx/inference/python |
 [Ds2 Offline Aishell ASR0 Model](https://paddlespeech.bj.bcebos.com/s2t/aishell/asr0/asr0_deepspeech2_offline_aishell_ckpt_1.0.1.model.tar.gz)| Aishell Dataset | Char-based | 1.4 GB | 2 Conv + 5 bidirectional LSTM layers| 0.0554 |-| 151 h | [Ds2 Offline Aishell ASR0](../../examples/aishell/asr0) | inference/python |
 [Conformer Online Wenetspeech ASR1 Model](https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr1/asr1_chunk_conformer_wenetspeech_ckpt_1.0.0a.model.tar.gz) | WenetSpeech Dataset | Char-based | 457 MB  | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring| 0.11 (test\_net) 0.1879 (test\_meeting) |-| 10000 h |- | python |
-[Conformer U2PP Online Wenetspeech ASR1 Model](https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr1/asr1_chunk_conformer_u2pp_wenetspeech_ckpt_1.1.4.model.tar.gz) | WenetSpeech Dataset | Char-based | 476 MB  | Encoder:Conformer, Decoder:BiTransformer, Decoding method: Attention rescoring| 0.047198 (aishell test\_-1) 0.059212 (aishell test\_16) |-| 10000 h |- | python |
+[Conformer U2PP Online Wenetspeech ASR1 Model](https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr1/asr1_chunk_conformer_u2pp_wenetspeech_ckpt_1.3.0.model.tar.gz) | WenetSpeech Dataset | Char-based | 476 MB  | Encoder:Conformer, Decoder:BiTransformer, Decoding method: Attention rescoring| 0.047198 (aishell test\_-1) 0.059212 (aishell test\_16) |-| 10000 h |- | python |
 [Conformer Online Aishell ASR1 Model](https://paddlespeech.bj.bcebos.com/s2t/aishell/asr1/asr1_chunk_conformer_aishell_ckpt_0.2.0.model.tar.gz) | Aishell Dataset | Char-based | 189 MB  | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring| 0.0544 |-| 151 h | [Conformer Online Aishell ASR1](../../examples/aishell/asr1) | python |
 [Conformer Offline Aishell ASR1 Model](https://paddlespeech.bj.bcebos.com/s2t/aishell/asr1/asr1_conformer_aishell_ckpt_1.0.1.model.tar.gz) | Aishell Dataset | Char-based | 189 MB  | Encoder:Conformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.0460 |-| 151 h | [Conformer Offline Aishell ASR1](../../examples/aishell/asr1) | python |
 [Transformer Aishell ASR1 Model](https://paddlespeech.bj.bcebos.com/s2t/aishell/asr1/asr1_transformer_aishell_ckpt_0.1.1.model.tar.gz) | Aishell Dataset | Char-based | 128 MB | Encoder:Transformer, Decoder:Transformer, Decoding method: Attention rescoring | 0.0523 || 151 h | [Transformer  Aishell ASR1](../../examples/aishell/asr1) | python |

paddlespeech/cli/asr/infer.py

@@ -52,7 +52,7 @@ class ASRExecutor(BaseExecutor):
         self.parser.add_argument(
             '--model',
             type=str,
-            default='conformer_u2pp_wenetspeech',
+            default='conformer_u2pp_online_wenetspeech',
             choices=[
                 tag[:tag.index('-')]
                 for tag in self.task_resource.pretrained_models.keys()
@@ -470,7 +470,7 @@ class ASRExecutor(BaseExecutor):
     @stats_wrapper
     def __call__(self,
                  audio_file: os.PathLike,
-                 model: str='conformer_u2pp_wenetspeech',
+                 model: str='conformer_u2pp_online_wenetspeech',
                  lang: str='zh',
                  sample_rate: int=16000,
                  config: os.PathLike=None,

paddlespeech/resource/model_alias.py

@@ -25,7 +25,6 @@ model_alias = {
     "deepspeech2online": ["paddlespeech.s2t.models.ds2:DeepSpeech2Model"],
     "conformer": ["paddlespeech.s2t.models.u2:U2Model"],
     "conformer_online": ["paddlespeech.s2t.models.u2:U2Model"],
-    "conformer_u2pp": ["paddlespeech.s2t.models.u2:U2Model"],
     "conformer_u2pp_online": ["paddlespeech.s2t.models.u2:U2Model"],
     "transformer": ["paddlespeech.s2t.models.u2:U2Model"],
     "wenetspeech": ["paddlespeech.s2t.models.u2:U2Model"],

paddlespeech/resource/pretrained_models.py

@@ -68,32 +68,12 @@ asr_dynamic_pretrained_models = {
             '',
         },
     },
-    "conformer_u2pp_wenetspeech-zh-16k": {
-        '1.1': {
-            'url':
-            'https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr1/asr1_chunk_conformer_u2pp_wenetspeech_ckpt_1.1.3.model.tar.gz',
-            'md5':
-            '662b347e1d2131b7a4dc5398365e2134',
-            'cfg_path':
-            'model.yaml',
-            'ckpt_path':
-            'exp/chunk_conformer_u2pp/checkpoints/avg_10',
-            'model':
-            'exp/chunk_conformer_u2pp/checkpoints/avg_10.pdparams',
-            'params':
-            'exp/chunk_conformer_u2pp/checkpoints/avg_10.pdparams',
-            'lm_url':
-            '',
-            'lm_md5':
-            '',
-        },
-    },
     "conformer_u2pp_online_wenetspeech-zh-16k": {
-        '1.1': {
+        '1.3': {
             'url':
-            'https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr1/asr1_chunk_conformer_u2pp_wenetspeech_ckpt_1.1.4.model.tar.gz',
+            'https://paddlespeech.bj.bcebos.com/s2t/wenetspeech/asr1/asr1_chunk_conformer_u2pp_wenetspeech_ckpt_1.3.0.model.tar.gz',
             'md5':
-            '3100fc1eac5779486cab859366992d0b',
+            '62d230c1bf27731192aa9d3b8deca300',
             'cfg_path':
             'model.yaml',
             'ckpt_path':