Semantic Role Labeling in Indonesian Texting Language using Deep Learning
Semantic Role Labeling (SRL) is a task in Natural Language Processing (NLP) which aims to automatically assign semantic roles to each argument for each predicate in a given input sentence. Even though SRL research on English language has been getting firmer throughout years, the number of research on Indonesian language SRL is still low. In the field of chat-bot, the most natural way Indonesian use to communicate on chatting platform is the informal texting language. Moreover, Deep Learning approach for solving SRL has been proven to do the task effectively. Hence, we find it interesting to understand Indonesian informal text better through SRL using Deep Learning.
Valdi Rachman is a final year student at University of Indonesia majoring in Computer Science. His international experience includes having a student exchange scholarship program at National University of Singapore, taking Computer Vision and Pattern Recognition course. He has been active in leadership activities as seen from his participation as one of the Indonesian delegates for the TFI LEaRN Young Asian Leaders Forum 2016 at Nanyang Technological University. His current research involves the study of semantic role labeling in Indonesian informal texting language using deep learning approach, as a research collaboration between Kata.ai and University of Indonesia.