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wanchichen_fleurs_multilingual_asr_hubert_frontend
espnet/wanchichen_fleurs_multilingual_asr_hubert_frontend
wanchichen_fleurs_multilingual_asr_hubert_frontend is a automatic speech recognition model from espnet. Use it when you need speech turned into text. It is set up for espnet. The card lists the license as cc-by-4.0.
This model was trained by William Chen using the fleurs recipe in espnet.
All-time downloads
184
Public
Repo size
1.6 GB
Likes
2
Public
Repo makeup
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.pth1.6 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- espnet
- License
- cc-by-4.0
- Access
- Public
- Created
- Aug 24, 2022
- Updated
- Sep 19, 2026
- SHA
- e0c99f03
Datasets
Model card
From the Hugging Face model README
Usage
import librosa
from espnet2.bin.asr_inference import Speech2Text
speech2text = Speech2Text.from_pretrained(model_tag="espnet/wanchichen_fleurs_multilingual_asr_hubert_frontend")
# librosa resamples and mixes to one channel, so any file works; 16000 is
# what nearly every espnet recogniser is trained on - check this model's
# config if its audio is not 16 kHz
speech, rate = librosa.load("audio.wav", sr=16000, mono=True)
text, *_ = speech2text(speech)[0]
print(text)
ESPnet2 ASR model
espnet/wanchichen_fleurs_multilingual_asr_hubert_frontend
This model was trained by William Chen using the fleurs recipe in espnet.
Demo: How to use in ESPnet2
cd espnet
pip install -e .
cd egs2/fleurs/asr1
./run.sh
RESULTS
Environments
- date:
Sun Aug 21 15:18:30 EDT 2022 - python version:
3.8.6 (default, Dec 17 2020, 16:57:01) [GCC 10.2.0] - espnet version:
espnet 202205 - pytorch version:
pytorch 1.8.1+cu102 - Git hash:
45e8cb9173a072f85ee7a7ccbcae06af7c5c484a- Commit date:
Wed Jun 1 14:21:14 2022 +0900
- Commit date:
asr_train_asr_hubert_raw_all_raw_all_bpe6500_sp
WER
| dataset | Snt | Wrd | Corr | Sub | Del | Ins | Err | S.Err |
|---|---|---|---|---|---|---|---|---|
| decode_asr_asr_model_valid.acc.best/test_all | 77809 | 1669969 | 54.2 | 38.1 | 7.8 | 4.0 | 49.9 | 99.7 |
| decode_asr_asr_model_valid.acc.best/dev_all | 31622 | 610500 | 53.4 | 38.7 | 7.9 | 3.5 | 50.1 | 99.5 |
CER
| dataset | Snt | Wrd | Corr | Sub | Del | Ins | Err | S.Err |
|---|---|---|---|---|---|---|---|---|
| decode_asr_asr_model_valid.acc.best/test_all | 77809 | 10876592 | 85.1 | 7.4 | 7.5 | 3.2 | 18.0 | 99.7 |
| decode_asr_asr_model_valid.acc.best/dev_all | 31622 | 3988181 | 84.7 | 7.7 | 7.7 | 2.8 | 18.1 | 99.5 |
TER
| dataset | Snt | Wrd | Corr | Sub | Del | Ins | Err | S.Err |
|---|---|---|---|---|---|---|---|---|
| decode_asr_asr_model_valid.acc.best/test_all | 77809 | 9622352 | 82.8 | 9.2 | 8.0 | 3.4 | 20.6 | 99.7 |
| decode_asr_asr_model_valid.acc.best/dev_all | 31622 | 3547834 | 82.4 | 9.4 | 8.2 | 3.0 | 20.6 | 99.5 |
- Task
- Automatic Speech Recognition
- Library
- espnet
- License
- cc-by-4.0
- Languages
- en
- Created
- Aug 24, 2022
- Updated
- Sep 19, 2026