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---
base_model: utter-project/mHuBERT-147
license: cc-by-nc-sa-4.0
language:
- uk
tags:
- automatic-speech-recognition
datasets:
- espnet/yodas2
metrics:
- wer
model-index:
- name: w2v-bert-2.0-uk-v2.1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_10_0
type: common_voice_10_0
config: uk
split: test
args: uk
metrics:
- name: WER
type: wer
value: 37.07
- name: CER
type: cer
value: 6.87
---
# HuBERT for Ukrainian
## Community
- Discord: https://bit.ly/discord-uds
- Speech Recognition: https://t.me/speech_recognition_uk
- Speech Synthesis: https://t.me/speech_synthesis_uk
See other Ukrainian models: https://github.com/egorsmkv/speech-recognition-uk
## Install
```text
uv venv --python 3.12
source .venv/bin/activate
uv pip install -r requirements.txt
uv pip install -r requirements-dev.txt
```
## Evaluation results
Metrics (float16) using `evaluate` library:
- WER: 0.3707 metric, 37.07%
- CER: 0.0687 metric, 6.87%
- Accuracy on words: 62.93%
- Accuracy on chars: 93.13%
- Inference time: 43.0227 seconds
- Audio duration: 16665.5212 seconds
- RTF: 0.0026
## Cite this work
```
@misc {smoliakov_2025,
author = { {Smoliakov} },
title = { hubert-uk (Revision 4aae976) },
year = 2025,
url = { https://huggingface.co/Yehor/hubert-uk },
doi = { 10.57967/hf/4557 },
publisher = { Hugging Face }
}
``` |