Add images

README.md

@@ -10,7 +10,7 @@ Speech transcripts generated by Automatic Speech Recognition (ASR) systems typic
 
 The purpose of this task is to restore punctuation in the ASR recognition of texts read out loud.
 
-![](https://github.com/poleval/2021-punctuation-restoration-prepare/tree/main/img/image001.png)
+![](https://poleval.github.io/2021-punctuation-restoration/img/image001.png)
 
 ## Dataset – WikiPunct
 
@@ -194,13 +194,13 @@ The output to be evaluated is just the text with punctuation marks added.
 Final results are evaluated in terms of precision, recall, and F1 scores for predicting each punctuation mark separately. Submissions are compared with respect to the weighted average of F1 scores for each punctuation sign.
 
 ##### Per-document score:
-![](https://github.com/poleval/2021-punctuation-restoration-prepare/tree/main/img/image003.png)
+![](https://poleval.github.io/2021-punctuation-restoration/img/image003.png)
 
 ##### Global score per punctuation sign _p_:
-![](https://github.com/poleval/2021-punctuation-restoration-prepare/tree/main/img/image005.png)
+![](https://poleval.github.io/2021-punctuation-restoration/img/image005.png)
 
 Final scoring metric calculated as weighted average of global scores per
-![](https://github.com/poleval/2021-punctuation-restoration-prepare/tree/main/img/image007.png)
+![](https://poleval.github.io/2021-punctuation-restoration/img/image007.png)
 
 We would like to invite participants to discussion about evaluation metrics, taking into account such factors as: