metadata
base_model: facebook/wav2vec2-xls-r-300m
language:
- uk
license: apache-2.0
tags:
- automatic-speech-recognition
datasets:
- mozilla-foundation/common_voice_10_0
metrics:
- wer
model-index:
- name: w2v-xls-r-uk
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: 20.24
- name: CER
type: cer
value: 3.64
🚨🚨🚨 ATTENTION! 🚨🚨🚨
Use an updated model: https://huggingface.co/Yehor/w2v-bert-uk-v2.1
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
Evaluation results
Metrics (float16) using evaluate library with batch_size=1:
- WER: 0.2024 metric, 20.24%
- CER: 0.0364 metric, 3.64%
- Accuracy on words: 79.76%
- Accuracy on chars: 96.36%
- Inference time: 63.4848 seconds
- Audio duration: 16665.5212 seconds
- RTF: 0.0038
Cite this work
@misc {smoliakov_2025,
author = { {Smoliakov} },
title = { w2v-xls-r-uk (Revision 55b6dc0) },
year = 2025,
url = { https://huggingface.co/Yehor/w2v-xls-r-uk },
doi = { 10.57967/hf/4556 },
publisher = { Hugging Face }
}