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58AILab/wenet_efficient_conformer_librispeech_v1
wenet_efficient_conformer_librispeech_v1 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 | 3.65 | 3.88 | 3.87 |
| ctc_greedy_search | 3.46 | 3.79 | 3.77 |
| ctc prefix beam search | 3.44 | 3.75 | 3.74 |
| attention rescoring | 3.17 | 3.44 | 3.41 |
test other
| decoding mode | full | 18 | 16 |
|---|---|---|---|
| attention decoder | 8.51 | 9.24 | 9.25 |
| ctc_greedy_search | 8.94 | 10.04 | 10.06 |
| ctc prefix beam search | 8.91 | 10 | 10.01 |
| attention rescoring | 8.21 | 9.25 | 9.25 |
Install WeNet follow: https://wenet.org.cn/wenet/install.html#install-for-training
Decode
cd examples/librispeech/s0
cp exp/wenet_efficient_conformer_librispeech_v1/decode.sh ./
cp exp/wenet_efficient_conformer_librispeech_v1/wer.sh ./
dir=exp/wenet_efficient_conformer_librispeech_v1
decoding_chunk_size=-1
. ./decode.sh ${dir} 20 ${decoding_chunk_size}
# WER
. ./wer.sh test_clean wenet_efficient_conformer_librispeech_v1 ${decoding_chunk_size}
. ./wer.sh test_other wenet_efficient_conformer_librispeech_v1 ${decoding_chunk_size}