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

amphibian

江湖郎中

骯臟

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.

Rejuvenate

考博

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.

笨拙的我

笨拙的你

figure

通情達(dá)理

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.

Lipohypertrophy

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