
**NOTE**: Look on a better model https://huggingface.co/Yehor/wav2vec2-xls-r-base-uk-with-cv-lm

🇺🇦 Join Ukrainian Speech Recognition Community - https://t.me/speech_recognition_uk

⭐ See other Ukrainian models - https://github.com/egorsmkv/speech-recognition-uk

This model was trained using the base model https://huggingface.co/fav-kky/wav2vec2-base-cs-80k-ClTRUS (pre-trained from 80 thousand hours of Czech speech)

This model has apostrophes and hyphens.

Metrics:


Without LM:

- WER: 0.4745
- CER: 0.1104

---

SMALL LM (this repository):

- WER: 0.303
- CER: 0.0818
 
WIKI LM (https://huggingface.co/Yehor/wav2vec2-xls-r-300m-uk-with-wiki-lm/tree/main/language_model):

- WER: 0.2807
- CER: 0.0785

NEWS LM (https://huggingface.co/Yehor/wav2vec2-xls-r-300m-uk-with-news-lm/tree/main/language_model):

- WER: 0.2633
- CER: 0.0753



{"language": ["uk"], "license": "cc-by-nc-sa-4.0"}
transformers pytorch wav2vec2 automatic-speech-recognition uk license:cc-by-nc-sa-4.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #uk #license-cc-by-nc-sa-4.0 #endpoints_compatible #region-us 


NOTE: Look on a better model URL

🇺🇦 Join Ukrainian Speech Recognition Community - https://t.me/speech_recognition_uk

⭐ See other Ukrainian models - URL

This model was trained using the base model URL (pre-trained from 80 thousand hours of Czech speech)

This model has apostrophes and hyphens.

Metrics:


Without LM:

- WER: 0.4745
- CER: 0.1104

---

SMALL LM (this repository):

- WER: 0.303
- CER: 0.0818
 
WIKI LM (URL

- WER: 0.2807
- CER: 0.0785

NEWS LM (URL

- WER: 0.2633
- CER: 0.0753



TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #uk #license-cc-by-nc-sa-4.0 #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #uk #license-cc-by-nc-sa-4.0 #endpoints_compatible #region-us 
