JOINT ACOUSTIC AND SUPERVISED INFERENCE FOR SOUND EVENT DETECTION Technical Report

This is a technical report about a sound event detection system for the task 4 of DCASE2020. The purpose of a sound event detection is to find event class label as well as its time boundaries. To achieve this purpose, we considered several methods such signal enhancement and event boundary detection, and built five systems by integrating these methods with supervised system trained by using Mean Teacher model. In particular, we estimate event boundaries of weakly labeled data by performing a event boundary detection. Then, we used the estimated strong label in training the supervised system. In addition, we adopt a fusion method by calculating weighted averaging posterior over the five outputs from each individual system. In experiments with validation set, we found that a final result of our system shows an improvement about 11 % in class averaging f-score compared to a baseline performance.