Detecting Racist Text in Bengali: An Ensemble Deep Learning Framework
원문 초록
Racism is an alarming phenomenon in our country as well as all over the world. Every day we have come across some racist comments in our daily life and virtual life. Though we can eradicate this racism from virtual life (such as Social Media). In this paper, we have tried to detect those racist comments with NLP and deep learning techniques. We have built a novel dataset in the Bengali Language. Further, we annotated the dataset and conducted data label validation. After extensive utilization of deep learning methodologies, we have successfully achieved text detection with an impressive accuracy rate of 87.94\% using the Ensemble approach. We have applied RNN and LSTM models using BERT Embeddings. However, the MCNN-LSTM model performed highest among all those models. Lastly, the Ensemble approach has been followed to combine all the model results to increase overall performance.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Slim attention: cut your context memory in half without loss -- K-cache is all you need for MHA
Is Diversity All You Need for Scalable Robotic Manipulation?
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language
These are Not All the Features You are Looking For: A Fundamental Bottleneck In Supervised Pretraining
Visual-Instructed Degradation Diffusion for All-in-One Image Restoration
토론
이 논문과 연결된 포럼 글이 아직 없습니다.