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Filip Gralinski 2021-05-28 17:35:16 +02:00
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README.md
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## Punctuation restoration from read text # Punctuation restoration from read text
Restore punctuation marks from the output of an ASR system.
## Motivation ## Motivation
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The purpose of this task is to restore punctuation in the ASR recognition of texts read out loud. The purpose of this task is to restore punctuation in the ASR recognition of texts read out loud.
![](img/image001.png) ![](https://github.com/poleval/2021-punctuation-restoration-prepare/tree/main/img/image001.png)
## Dataset – WikiPunct ## Dataset – WikiPunct
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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. 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: ##### Per-document score:
![](img/image003.png) ![](https://github.com/poleval/2021-punctuation-restoration-prepare/tree/main/img/image003.png)
##### Global score per punctuation sign _p_: ##### Global score per punctuation sign _p_:
![](img/image005.png) ![](https://github.com/poleval/2021-punctuation-restoration-prepare/tree/main/img/image005.png)
Final scoring metric calculated as weighted average of global scores per Final scoring metric calculated as weighted average of global scores per
![](img/image007.png) ![](https://github.com/poleval/2021-punctuation-restoration-prepare/tree/main/img/image007.png)
We would like to invite participants to discussion about evaluation metrics, taking into account such factors as: We would like to invite participants to discussion about evaluation metrics, taking into account such factors as: