Update README.md

README.md

@@ -1,7 +1,7 @@
 ---
 language: hr
 datasets:
-- parlaspeech
+- parlaspeech-hr
 tags:
 - audio
 - automatic-speech-recognition
@@ -16,9 +16,9 @@ widget:
 
 # wav2vec2-xls-r-parlaspeech-hr
 
-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.
+This model is based on the [facebook/wav2vec2-xls-r-300m model](https://huggingface.co/facebook/wav2vec2-xls-r-300m) and was fine-tuned with 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 the name ParlaSpeech-HR and an open licence.
 
-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.
+The efforts resulting in 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.
 
 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%.