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Titlebook: Computational Processing of the Portuguese Language; 14th International C Paulo Quaresma,Renata Vieira,Teresa Gonçalves Conference proceedi

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Sanchay Roy,Knut Alicke,Maren Forstingploratory work revisits what is already done and tests different tools to detect errors and look for the best methods to tackle the problem. Data is available at ., and it will be continuously improved.
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Native Language Identification on L2 Portuguesepact of different lexical representations, the use of syntactic dependencies and the performance of diverse classification methods. Our best model achieves an accuracy of 0.66 including lexical features, and of 0.61 excluding them. Both results improve previous works on NLI for L2 Portuguese.
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Fake News Detection on Fake.Br Using Hierarchical Attention Networks (90% accuracy) to the baseline established by the simple machine learning methods presented in the original presentation work of the Fake.Br (89% accuracy). Overall, keeping or removing stop words and varying the size of the word embeddings also shows a negligible advantage.
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Towards Automatic Determination of Critical Gestures for European Portuguese Soundstanding of the static and dynamic aspects of speech, namely by providing information regarding which articulators are essential (critical) in producing specific sounds and how (gestures). Previous work has successfully demonstrated the possibility to determine critical articulators considering vocal
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