Automatic Speech Recognition
speechbrain
PyTorch
English
wav2vec2
CTC
Attention
Transformer
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use speechbrain/asr-wav2vec2-librispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- speechbrain
How to use speechbrain/asr-wav2vec2-librispeech with speechbrain:
from speechbrain.pretrained import EncoderASR model = EncoderASR.from_hparams( "speechbrain/asr-wav2vec2-librispeech" ) model.transcribe_file("file.wav") - Notebooks
- Google Colab
- Kaggle
Update hyperparams_develop.yaml
Browse files- hyperparams_develop.yaml +1 -0
hyperparams_develop.yaml
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@@ -53,6 +53,7 @@ encoder: !new:speechbrain.nnet.containers.LengthsCapableSequential
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wav2vec2: !ref <wav2vec2>
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enc: !ref <enc>
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ctc_lin: !ref <ctc_lin>
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decoding_function: !name:speechbrain.decoders.ctc_greedy_decode
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blank_id: !ref <blank_index>
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wav2vec2: !ref <wav2vec2>
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enc: !ref <enc>
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ctc_lin: !ref <ctc_lin>
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log_softmax: !ref <log_softmax>
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decoding_function: !name:speechbrain.decoders.ctc_greedy_decode
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blank_id: !ref <blank_index>
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