Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text frontend, Speaker Verification System, End-to-End Speech Translation and Keyword Spotting. Won NAACL2022 Best Demo Award.
我解析出来结果不正确,我用的conformer_online_wenetspeech模型,把原来是16000改成了8000,以下是我的配置文件:
`asr_online:
model_type: 'conformer_online_wenetspeech'
am_model: # the pdmodel file of am static model [optional]
am_params: # the pdiparams file of am static model [optional]
lang: 'zh'
sample_rate: 8000
cfg_path:
decode_method:
force_yes: True
device: 'cpu' # cpu or gpu:id
decode_method: "attention_rescoring"
continuous_decoding: True # enable continue decoding when endpoint detected
num_decoding_left_chunks: -1
am_predictor_conf:
device: # set 'gpu:id' or 'cpu'
switch_ir_optim: True
glog_info: False # True -> print glog
summary: True # False -> do not show predictor config
我解析出来结果不正确,我用的conformer_online_wenetspeech模型,把原来是16000改成了8000,以下是我的配置文件: `asr_online: model_type: 'conformer_online_wenetspeech' am_model: # the pdmodel file of am static model [optional] am_params: # the pdiparams file of am static model [optional] lang: 'zh' sample_rate: 8000 cfg_path: decode_method: force_yes: True device: 'cpu' # cpu or gpu:id decode_method: "attention_rescoring" continuous_decoding: True # enable continue decoding when endpoint detected num_decoding_left_chunks: -1 am_predictor_conf: device: # set 'gpu:id' or 'cpu' switch_ir_optim: True glog_info: False # True -> print glog summary: True # False -> do not show predictor config
我该如何进行调整??