Abstractive Headline Generation from Bangla News Articles Using Seq2Seq RNNs with Global Attention

Headline generation is the process of generating headlines automatically from text articles. We model a comprehensive abstractive headline generation technique using Seq2Seq Recurrent Neural Networks with Global Attention in this work. Despite being one of the most spoken languages globally, very few significant works have been done on this particular topic in the Bangla language. Thus, our model is solely based on the Bangla language, and we find that the performance of the model is highly satisfactory at the current stage. We also propose an extensive dataset consisting of 5,14,108 filtered Bangla news articles in full and other necessary information. The dataset has been created by scrapping several online reputed Bangla newspapers. Due to the unavailability of a proper and updated dataset, the proposed datasets are freely available at https://tinyurl.com/banglaHead