Sanskrit Poetry

Research on Sanskrit poetry is leveraging computational linguistics to analyze and understand its rich structure and aesthetic qualities, focusing on tasks like word segmentation, compound identification, and dependency parsing. Current efforts employ neural network architectures, including multi-task learning models and sequence-to-sequence models, to process the language's complexities, such as compounding and sandhi. These advancements facilitate the creation of knowledge graphs and question-answering systems, improving access to and understanding of this vast literary corpus, while also contributing to broader advancements in natural language processing for low-resource languages.