most citedExploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish

3 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

eess.AS2022

Remap, warp and attend: Non-parallel many-to-many accent conversion with Normalizing Flows

Abdelhamid Ezzerg, Thomas Merritt, Kayoko Yanagisawa +6

Regional accents of the same language affect not only how words are pronounced (i.e., phonetic content), but also impact prosodic aspects of speech such as speaking rate and intona…

cs.CL2019★ 3 cited

Exploiting Unsupervised Pre-training and Automated Feature Engineering for Low-resource Hate Speech Detection in Polish

Renard Korzeniowski, Rafał Rolczyński, Przemysław Sadownik +2

This paper presents our contribution to PolEval 2019 Task 6: Hate speech and bullying detection. We describe three parallel approaches that we followed: fine-tuning a pre-trained U…