提交 050d7669 编写于 作者: T tianhao zhang

fix u2pp model

上级 1b9b1f54
......@@ -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 |
......
......@@ -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,
......
......@@ -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"],
......
......@@ -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':
......
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