nljubesi commited on
Commit
e84eba9
1 Parent(s): 99a28ed

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +2 -2
README.md CHANGED
@@ -15,8 +15,8 @@ widget:
15
 
16
  # wav2vec2-xls-r-sabor-hr
17
 
18
- This model is based on the [facebook/wav2vec2-xls-r-300m model](https://huggingface.co/facebook/wav2vec2-xls-r-300m) and was fine-tuned over 72 hours of recordings and transcripts from the Croatian parliament. These transcripts are an early result of the second iteration of the [ParlaMint project](https://www.clarin.eu/content/parlamint-towards-comparable-parliamentary-corpora) and will be extended and published under a permissive license.
19
 
20
- These efforts were coordinated by Nikola Ljubešić, the manual data alignment was performed by Ivo-Pavao Jazbec, the method from [Plüss et al](https://arxiv.org/abs/2010.02810) was applied by Vuk Batanović and Lenka Bajčetić, while the final modelling was performed by Peter Rupnik.
21
 
22
  Initial evaluation on partially noisy data showed the model to achieve a word error rate of 13.68% and a character error rate of 4.56%.
15
 
16
  # wav2vec2-xls-r-sabor-hr
17
 
18
+ This model is based on the [facebook/wav2vec2-xls-r-300m model](https://huggingface.co/facebook/wav2vec2-xls-r-300m) and was fine-tuned over 72 hours of recordings and transcripts from the Croatian parliament. This training dataset is an early result of the second iteration of the [ParlaMint project](https://www.clarin.eu/content/parlamint-towards-comparable-parliamentary-corpora) inside which the dataset will be extended and published under a permissive license.
19
 
20
+ The efforts resulting with this model were coordinated by Nikola Ljubešić, the rough manual data alignment was performed by Ivo-Pavao Jazbec, the method for fine automatic data alignment from [Plüss et al.](https://arxiv.org/abs/2010.02810) was applied by Vuk Batanović and Lenka Bajčetić, while the final modelling was performed by Peter Rupnik.
21
 
22
  Initial evaluation on partially noisy data showed the model to achieve a word error rate of 13.68% and a character error rate of 4.56%.