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Update app.py
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app.py
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@@ -105,21 +105,20 @@ title = """
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"""
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description = """
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<ul>
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<li>"<em>mar7aba!</em>"</li>
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<li>"<em>هاو ئار یوو؟</em>"</li>
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<li>"<em>Μπιάνβενου α σετ ντεμό!</em>"</li>
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</ul>
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<p>What all these sentences are in common? Being greeted in Arabic with "<em>mar7aba</em>" written in the Latin script, then asked how you are ("<em>هاو ئار یوو؟</em>") in English using the Perso-Arabic script of Kurdish and then, welcomed to this demo in French ("<em>Μπιάνβενου α σετ ντεμό!</em>") written in Greek script. All these sentences are written in an <strong>unconventional</strong> script.</p>
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<p>Although you may find these sentences risible, unconventional writing is a common practice among millions of speakers in bilingual communities. In our paper entitled "<a href="https://sinaahmadi.github.io/docs/articles/ahmadi2023acl.pdf" target="_blank"><strong>Script Normalization for Unconventional Writing of Under-Resourced Languages in Bilingual Communities</strong></a>", we shed light on this problem and propose an approach to normalize noisy text written in unconventional writing.</p>
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<p>This demo deploys a few models that are trained for <strong>the normalization of unconventional writing</strong>. Please note that this tool is not a spell-checker and cannot correct errors beyond character normalization. For better performance, you can apply hard-coded rules on the input and then pass it to the models, hence a hybrid system.</p>
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For more information, you can check out the project on GitHub too: <a href="https://github.com/sinaahmadi/ScriptNormalization" target="_blank"><strong>https://github.com/sinaahmadi/ScriptNormalization</strong></a>
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</div>
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"""
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examples = [
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"""
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description = """
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<ul>
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<li style="font-size:160%;">"<em>mar7aba!</em>"</li>
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<li style="font-size:160%;">"<em>هاو ئار یوو؟</em>"</li>
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<li style="font-size:160%;">"<em>Μπιάνβενου α σετ ντεμό!</em>"</li>
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</ul>
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<p style="font-size:160%;">What all these sentences are in common? Being greeted in Arabic with "<em>mar7aba</em>" written in the Latin script, then asked how you are ("<em>هاو ئار یوو؟</em>") in English using the Perso-Arabic script of Kurdish and then, welcomed to this demo in French ("<em>Μπιάνβενου α σετ ντεμό!</em>") written in Greek script. All these sentences are written in an <strong>unconventional</strong> script.</p>
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<p style="font-size:160%;">Although you may find these sentences risible, unconventional writing is a common practice among millions of speakers in bilingual communities. In our paper entitled "<a href="https://sinaahmadi.github.io/docs/articles/ahmadi2023acl.pdf" target="_blank"><strong>Script Normalization for Unconventional Writing of Under-Resourced Languages in Bilingual Communities</strong></a>", we shed light on this problem and propose an approach to normalize noisy text written in unconventional writing.</p>
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<p style="font-size:160%;">This demo deploys a few models that are trained for <strong>the normalization of unconventional writing</strong>. Please note that this tool is not a spell-checker and cannot correct errors beyond character normalization. For better performance, you can apply hard-coded rules on the input and then pass it to the models, hence a hybrid system.</p>
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For more information, you can check out the project on GitHub too: <a href="https://github.com/sinaahmadi/ScriptNormalization" target="_blank"><strong>https://github.com/sinaahmadi/ScriptNormalization</strong></a>
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"""
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examples = [
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