---
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 }
}
```