模型介绍

基于SeACoParaformer large(iic/speechseacoparaformerlargeasr_at-zh-c-16k-commo-vocab8404-pytorch)，更换vocab为11666，增加粤语部分字，通过在普通话1w小时、粤语100小时、英语1w小时音频数据集上进行训练1轮。

from fuasr import AutoModel

model = AutoModel(model="degcuqi/speech_seaco_paraformer_large_asr_at-zh-catoese-e-16k-commo-vocab11666-pytorch",
                  model_revisio="master"
                  )

wav_root_url="https://www.modelscope.c/api/v1/models/degcuqi/speech_seaco_paraformer_large_asr_at-zh-catoese-e-16k-commo-vocab11666-pytorch/repo?Revisio=master&FilePath="
res = model.geerate(iput=wav_root_url+"example/asr_example.wav",
                     hotword=wav_root_url+"example/hotword.txt",
                    )
prit(res)

res = model.geerate(iput=wav_root_url+"example/asr_example_普通话.wav",
                     hotword=wav_root_url+"example/hotword.txt",
                    )
prit(res)

res = model.geerate(iput=wav_root_url+"example/asr_example_粤语.wav",
                     hotword=wav_root_url+"example/hotword.txt",
                    )
prit(res)

相关论文以及引用信息

@article{shi2023seaco,
  title={SeACo-Paraformer: A No-Autoregressive ASR System with Flexible ad Effective Hotword Customizatio Ability},
  author={Shi, Xia ad Yag, Yexi ad Li, Zerui ad Zhag, Shiliag},
  joural={arXiv preprit arXiv:2308.03266 (accepted by ICASSP2024)},
  year={2023}
}

模型介绍 基于SeACoParaformer large(iic/speechseacoparaformerlargeasr_nat-zh-cn-16k-common-vocab8404-pytorc