---
tags:
- espnet
- audio
- speech-recognition
- openai-whisper
language: en
datasets:
- chime4
license: cc-by-4.0
---

## ESPnet2 ASR model

### `espnet/shihlun_asr_whisper_medium_finetuned_chime4`
This model was trained by Shih-Lun Wu (slseanwu) using the chime4 recipe in [espnet](https://github.com/espnet/espnet/).

### Demo: How to use in ESPnet2
```bash
cd espnet
pip install -e .
cd egs2/chime4/asr1

train_set=tr05_multi_noisy_si284 # tr05_multi_noisy (original training data) or tr05_multi_noisy_si284 (add si284 data)
valid_set=dt05_multi_isolated_1ch_track
test_sets="dt05_real_isolated_1ch_track dt05_simu_isolated_1ch_track et05_real_isolated_1ch_track et05_simu_isolated_1ch_track"

asr_tag=whisper_medium_finetune_lr1e-5_adamw_wd1e-2_3epochs
asr_config=conf/tuning/train_asr_whisper_full.yaml
inference_config=conf/decode_asr_whisper_noctc_greedy.yaml

./asr.sh \
    --skip_data_prep false \
    --skip_train true \
    --skip_eval false \
    --lang en \
    --ngpu 1 \
    --nj 4 \
    --stage 1 \
    --stop_stage 13 \
    --gpu_inference true \
    --inference_nj 1 \
    --token_type whisper_multilingual \
    --feats_normalize '' \
    --max_wav_duration 30 \
    --feats_type raw \
    --use_lm false \
    --cleaner whisper_en \
    --asr_tag "${asr_tag}" \
    --asr_config "${asr_config}" \
    --inference_config "${inference_config}" \
    --inference_asr_model valid.acc.ave.pth \
    --train_set "${train_set}" \
    --valid_set "${valid_set}" \
    --test_sets "${test_sets}" "$@"
```

<!-- Generated by scripts/utils/show_asr_result.sh -->
# RESULTS
## Environments
- date: `Tue Jan 10 04:15:30 CST 2023`
- python version: `3.9.13 (main, Aug 25 2022, 23:26:10)  [GCC 11.2.0]`
- espnet version: `espnet 202211`
- pytorch version: `pytorch 1.12.1`
- Git hash: `d89be931dcc8f61437ac49cbe39a773f2054c50c`
  - Commit date: `Mon Jan 9 11:06:45 2023 -0600`

## asr_whisper_medium_finetune_lr1e-5_adamw_wd1e-2_3epochs
### WER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_asr_whisper_noctc_beam20_asr_model_valid.acc.ave/dt05_real_isolated_1ch_track|1640|24791|97.8|1.7|0.5|0.3|2.5|24.5|
|decode_asr_whisper_noctc_beam20_asr_model_valid.acc.ave/dt05_simu_isolated_1ch_track|1640|24792|96.1|3.0|0.9|0.5|4.4|35.6|
|decode_asr_whisper_noctc_beam20_asr_model_valid.acc.ave/et05_real_isolated_1ch_track|1320|19341|96.4|2.9|0.7|0.5|4.1|33.0|
|decode_asr_whisper_noctc_beam20_asr_model_valid.acc.ave/et05_simu_isolated_1ch_track|1320|19344|93.4|5.0|1.7|0.8|7.4|41.8|
|decode_asr_whisper_noctc_greedy_asr_model_valid.acc.ave/dt05_real_isolated_1ch_track|1640|24791|97.7|1.8|0.5|0.4|2.8|25.5|
|decode_asr_whisper_noctc_greedy_asr_model_valid.acc.ave/dt05_simu_isolated_1ch_track|1640|24792|96.0|3.3|0.8|0.7|4.8|36.0|
|decode_asr_whisper_noctc_greedy_asr_model_valid.acc.ave/et05_real_isolated_1ch_track|1320|19341|96.1|3.3|0.6|0.7|4.6|34.9|
|decode_asr_whisper_noctc_greedy_asr_model_valid.acc.ave/et05_simu_isolated_1ch_track|1320|19344|92.9|5.8|1.3|1.2|8.3|43.2|

### CER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_asr_whisper_noctc_beam20_asr_model_valid.acc.ave/dt05_real_isolated_1ch_track|1640|141889|99.1|0.3|0.5|0.3|1.2|24.5|
|decode_asr_whisper_noctc_beam20_asr_model_valid.acc.ave/dt05_simu_isolated_1ch_track|1640|141900|98.2|0.8|1.0|0.5|2.3|35.6|
|decode_asr_whisper_noctc_beam20_asr_model_valid.acc.ave/et05_real_isolated_1ch_track|1320|110558|98.5|0.7|0.8|0.5|1.9|33.0|
|decode_asr_whisper_noctc_beam20_asr_model_valid.acc.ave/et05_simu_isolated_1ch_track|1320|110572|96.5|1.6|1.9|0.8|4.3|41.8|
|decode_asr_whisper_noctc_greedy_asr_model_valid.acc.ave/dt05_real_isolated_1ch_track|1640|141889|99.1|0.4|0.5|0.5|1.3|25.5|
|decode_asr_whisper_noctc_greedy_asr_model_valid.acc.ave/dt05_simu_isolated_1ch_track|1640|141900|98.2|0.9|0.9|0.6|2.4|36.0|
|decode_asr_whisper_noctc_greedy_asr_model_valid.acc.ave/et05_real_isolated_1ch_track|1320|110558|98.4|0.9|0.7|0.6|2.2|34.9|
|decode_asr_whisper_noctc_greedy_asr_model_valid.acc.ave/et05_simu_isolated_1ch_track|1320|110572|96.3|2.0|1.7|1.2|4.9|43.2|