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

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

This model has been trained on noisy data in order to make the acoustic model robust to noisy audio data.

This model has apostrophes and hyphens.

The language model is trained on the texts of the Common Voice dataset, which is used during training.

Special thanks for noised data to **Dmytro Chaplynsky**, https://lang.org.ua

Noisy dataset:

- Transcriptions: https://www.dropbox.com/s/ohj3y2cq8f4207a/transcriptions.zip?dl=0
- Audio files: https://www.dropbox.com/s/v8crgclt9opbrv1/data.zip?dl=0

Metrics:

| Dataset | CER | WER |
|-|-|-|
| CV10 (no LM) | 0.0515 | 0.2617 |
| CV10 (with LM) | 0.0148 | 0.0524 |

Metrics on noisy data with [standard model](https://huggingface.co/Yehor/wav2vec2-xls-r-300m-uk-with-small-lm):

| Dataset | CER | WER |
|-|-|-|
| CV10 (no LM) | 0.1064 | 0.3926 |
| CV10 (with LM) | 0.0497 | 0.1265 |

More:

- The same model, but trained on raw Common Voice data: https://huggingface.co/Yehor/wav2vec2-xls-r-300m-uk-with-small-lm

{"language": ["uk"], "license": "apache-2.0", "datasets": ["mozilla-foundation/common_voice_10_0"]}
transformers pytorch wav2vec2 automatic-speech-recognition uk dataset:mozilla-foundation/common_voice_10_0 license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #uk #dataset-mozilla-foundation/common_voice_10_0 #license-apache-2.0 #endpoints_compatible #region-us 

🇺🇦 Join Ukrainian Speech Recognition Community - https://t.me/speech\_recognition\_uk


⭐ See other Ukrainian models - URL


This model has been trained on noisy data in order to make the acoustic model robust to noisy audio data.


This model has apostrophes and hyphens.


The language model is trained on the texts of the Common Voice dataset, which is used during training.


Special thanks for noised data to Dmytro Chaplynsky, URL


Noisy dataset:


* Transcriptions: URL
* Audio files: URL


Metrics:


Dataset: CV10 (no LM), CER: 0.0515, WER: 0.2617
Dataset: CV10 (with LM), CER: 0.0148, WER: 0.0524


Metrics on noisy data with standard model:


Dataset: CV10 (no LM), CER: 0.1064, WER: 0.3926
Dataset: CV10 (with LM), CER: 0.0497, WER: 0.1265


More:


* The same model, but trained on raw Common Voice data: URL



TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #uk #dataset-mozilla-foundation/common_voice_10_0 #license-apache-2.0 #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #wav2vec2 #automatic-speech-recognition #uk #dataset-mozilla-foundation/common_voice_10_0 #license-apache-2.0 #endpoints_compatible #region-us 
