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58AILab/wenet_efficient_conformer_librispeech_v2
wenet_efficient_conformer_librispeech_v2 is a automatic speech recognition model from 58AILab. Use it when you need speech turned into text. The card lists the license as apache-2.0.
Specification: https://github.com/wenet-e2e/wenet/pull/1636
Downloads · 30 days
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Updated Mar 21, 2023
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From the Hugging Face model README
Specification: https://github.com/wenet-e2e/wenet/pull/1636
test clean
| decoding mode | full | 18 | 16 |
|---|---|---|---|
| attention decoder | 3.49 | 3.71 | 3.72 |
| ctc_greedy_search | 3.49 | 3.74 | 3.77 |
| ctc prefix beam search | 3.47 | 3.72 | 3.74 |
| attention rescoring | 3.12 | 3.38 | 3.36 |
test other
| decoding mode | full | 18 | 16 |
|---|---|---|---|
| attention decoder | 8.15 | 9.05 | 9.03 |
| ctc_greedy_search | 8.73 | 9.82 | 9.83 |
| ctc prefix beam search | 8.70 | 9.81 | 9.79 |
| attention rescoring | 8.05 | 9.08 | 9.10 |
Install WeNet follow: https://wenet.org.cn/wenet/install.html#install-for-training
Decode
cd examples/librispeech/s0
cp exp/wenet_efficient_conformer_librispeech_v2/decode.sh ./
cp exp/wenet_efficient_conformer_librispeech_v2/wer.sh ./
dir=exp/wenet_efficient_conformer_librispeech_v2
decoding_chunk_size=-1
. ./decode.sh ${dir} 20 ${decoding_chunk_size}
# WER
. ./wer.sh test_clean wenet_efficient_conformer_librispeech_v2 ${decoding_chunk_size}
. ./wer.sh test_other wenet_efficient_conformer_librispeech_v2 ${decoding_chunk_size}