论文标题
Rabindranet，以Rabindranath Tagore的风格创作文学作品
RabindraNet, Creating Literary Works in the Style of Rabindranath Tagore
论文作者
论文摘要
孟加拉文学拥有数百年历史，其中包括Rabindranath Tagore和Kazi Nazrul Islam等亮度人物。但是，涉及NLP最新进步的分析作品几乎没有从语言作者那里收集的大量作品来刮擦表面。为了引起人们对涉及孟加拉作家的作品的分析研究，并以现有文学风格的文字生成努力为主角，我们正在介绍Rabindranet，这是一种具有堆积的LSTM模型的角色级别的RNN RNN，该模型对Rabindranath Tagore的作品进行了培训，可为他的多种流体制作文学作品。我们还通过从真实的在线资源中汇编了Rabindranath Tagore的数字化作品，并以数据科学平台Kaggle上的开源数据集发表，也创建了广泛的数据集。
Bengali literature has a rich history of hundreds of years with luminary figures such as Rabindranath Tagore and Kazi Nazrul Islam. However, analytical works involving the most recent advancements in NLP have barely scratched the surface utilizing the enormous volume of the collected works from the writers of the language. In order to bring attention to the analytical study involving the works of Bengali writers and spearhead the text generation endeavours in the style of existing literature, we are introducing RabindraNet, a character level RNN model with stacked-LSTM layers trained on the works of Rabindranath Tagore to produce literary works in his style for multiple genres. We created an extensive dataset as well by compiling the digitized works of Rabindranath Tagore from authentic online sources and published as open source dataset on data science platform Kaggle.
