| Proj No. | B3256-251 |
| Title | Air Traffic Control Discourse Analysis for Incident Investigation |
| Summary | This project focuses on analysing air traffic control communication for incident investigation by developing algorithms that extracts key events and construct timelines using LLM-based AI agents. The student will explore Whisper to transcribe ATC speech and leverage on classic Natural Language Processing (NLP) techniques like named entity recognition to process the output into identifiable entities before integrating with LLM-based AI agents to execute the overarching goal. Ultimately, produce a full detailed report evaluating key elements of the system and its effectiveness. Pre-requisite: Machine learning fundamentals (PyTorch/Scikit-learn/HuggingFace Transformers), Python Programming, Knowledge of aviation communication protocols. |
| Supervisor | Prof Cheng Tee Hiang (Loc:S1 > S1 B1C > S1 B1C 107, Ext: +65 67904534) |
| Co-Supervisor | - |
| RI Co-Supervisor | - |
| Lab | |
| Single/Group: | Single |
| Area: | Intelligent Systems and Control Engineering |
| ISP/RI/SMP/SCP?: | ISP: ME5 (Dr) Lim Yong Zhi Deputy Head of AETHER Republic of Singapore Air Force lim_yong_zhi1@defence.gov.sg |