Instructions to use pyf98/aishell_e_branchformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ESPnet
How to use pyf98/aishell_e_branchformer with ESPnet:
from espnet2.bin.asr_inference import Speech2Text model = Speech2Text.from_pretrained( "pyf98/aishell_e_branchformer" ) speech, rate = soundfile.read("speech.wav") text, *_ = model(speech)[0] - Notebooks
- Google Colab
- Kaggle
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This model was trained by Yifan Peng using aishell recipe in [espnet](https://github.com/espnet/espnet/).
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### Demo: How to use in ESPnet2
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Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
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This model was trained by Yifan Peng using aishell recipe in [espnet](https://github.com/espnet/espnet/).
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References:
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- [E-Branchformer: Branchformer with Enhanced merging for speech recognition (SLT 2022)](https://arxiv.org/abs/2210.00077)
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- [Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding (ICML 2022)](https://proceedings.mlr.press/v162/peng22a.htmlhttps://proceedings.mlr.press/v162/peng22a.html)
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### Demo: How to use in ESPnet2
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Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
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