metadata

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

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 }
}